Forest Soil-Water Resilience to Climate Change: Mechanisms and Management

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land, Soil and Water".

Deadline for manuscript submissions: 31 January 2026 | Viewed by 1238

Special Issue Editors


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Guest Editor
National Engineering Technology Research Center for Desert-Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
Interests: desertification control; water and soil conservation; agriculture technology; desert plant ecology; natural disaster risk assessment; climate change; land use models

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Guest Editor
Soils and Water Use Department, Agricultural and Biological Research Institute, National Research Centre (NRC), El-Behoos St., Dokki, Cairo 12622, Egypt
Interests: land evaluation; climate change models; spatiotemporal analysis of irrigation water quality; soil degradation; agriculture productivity; agroecological modelling and remote sensing techniques; soil carbon sequestration; adaptation strategies; improving soil characteristics; sustainable management; crop models and irrigation management
Special Issues, Collections and Topics in MDPI journals
Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
Interests: saline soils; halophyte; saline–alkali land restoration
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Climate change, especially global warming, has caused a marked increase in the frequency of compound drought and heatwave events and intense rainfall events, resulting in forest ecosystems facing severe challenges. Nevertheless, the interactions between soil, climate, and water continue to play vital roles in the stability of forest ecosystems. For example, mycorrhizal networks provide a mechanism for the redistribution of water into the upper soil layers experiencing low soil water potential, increasing drought resistance for their hosts. Natural mechanisms or artificial methods, including soil microfauna, rewilding, forest restoring, etc., have also clarified or enhanced the resilience of forest ecosystems; however, at the same time, many mechanisms or methods by which forest water–soil systems respond to climate change have yet to be explained.

The goal of this Special Issue is to collect papers (original research articles and review papers) that provide insights into the mechanisms of and methods by which forest soil–water system respond to climate change, with a particular focus on novel techniques or discoveries.

This Special Issue will welcome manuscripts that link the following themes:

  • Soil–water interaction mechanisms;
  • Forest ecosystem reforestation and afforestation;
  • Sustainable forest management;
  • Soil organic matter (SOM) and carbon sequestration;
  • Climate change impact models on ecosystems;
  • Forest ecological interaction;
  • Agriculture or forest models for land potential;
  • Management techniques or methods for responding to climate change.

We look forward to receiving your original research articles and reviews.

Dr. Jinglong Fan
Dr. Sameh Kotb Abd-Elmabod
Dr. Lei Wang
Guest Editors

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Keywords

  • climate change
  • ecosystem
  • ecological potential
  • interaction mechanisms
  • forest management
  • agriculture techniques
  • ecologic diversity

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Published Papers (2 papers)

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Research

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15 pages, 1348 KB  
Article
Ecological Risk Assessment of the Aksu River Basin Based on Ecological Service Value
by Guozhu Xia, Guanghui Lv and Jianjun Yang
Land 2025, 14(10), 2092; https://doi.org/10.3390/land14102092 - 21 Oct 2025
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Abstract
Understanding spatiotemporal dynamics and drivers of ecosystem service value (ESV) is critical for informing ecological restoration and sustainable land management, particularly in arid inland river basins. Analyzing the spatiotemporal dynamics of ESV in arid river basins and identifying key ecological and environmental drivers [...] Read more.
Understanding spatiotemporal dynamics and drivers of ecosystem service value (ESV) is critical for informing ecological restoration and sustainable land management, particularly in arid inland river basins. Analyzing the spatiotemporal dynamics of ESV in arid river basins and identifying key ecological and environmental drivers enable more precise diagnosis of ecological problems and provide a scientific basis for effective governance. This study evaluated the changes in ESV in the Aksu River Basin from 1990 to 2020 using the InVEST model, based on land use data, meteorological records, and biophysical parameters. A comprehensive assessment of seven key ecosystem services—including food production, water conservation, and biodiversity protection—was conducted. SHAP (SHapley Additive exPlanations) values were applied to interpret the contribution of ecological and environmental variables to ESV changes. The results showed that total ESV increased from CNY 18.904 billion in 1990 to a peak of CNY 22.323 billion in 2010, followed by a slight decline to CNY 20.806 billion in 2020. Spatially, Wensu, Xinhe, and Bachu counties exhibited substantial ESV gains, while Atushi, Akto, and Awat counties experienced significant losses. SHAP analysis identified forest quality, soil erosion, and grassland condition as the dominant drivers of ESV variation, surpassing the influence of land area alone. By combining biophysical modeling with interpretable machine learning, this study highlights the critical role of ecosystem quality rather than land area alone, offering a transferable approach for diagnosing ecological risk assessment in arid regions. Full article
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Review

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22 pages, 2870 KB  
Review
A Review of Biomass Estimation Methods for Forest Ecosystems in Kenya: Techniques, Challenges, and Future Perspectives
by Hamisi Tsama Mkuzi, Caleb Melenya Ocansey, Justin Maghanga, Miklós Gulyás, Károly Penksza, Szilárd Szentes, Erika Michéli, Márta Fuchs and Norbert Boros
Land 2025, 14(9), 1873; https://doi.org/10.3390/land14091873 - 13 Sep 2025
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Abstract
Accurate forest biomass estimation is essential for quantifying carbon stocks, guiding sustainable forest management, and informing climate change mitigation strategies. Kenya’s forests are diverse, ranging from Afromontane and mangrove ecosystems to dryland woodlands and plantations, each presenting unique challenges for biomass measurement. This [...] Read more.
Accurate forest biomass estimation is essential for quantifying carbon stocks, guiding sustainable forest management, and informing climate change mitigation strategies. Kenya’s forests are diverse, ranging from Afromontane and mangrove ecosystems to dryland woodlands and plantations, each presenting unique challenges for biomass measurement. This review synthesizes literature on field-based, remote sensing, and machine learning approaches applied in Kenya, highlighting their effectiveness, limitations, and integration potential. A systematic search across multiple databases identified peer-reviewed studies published in the last decade, screened against defined inclusion and exclusion criteria. The main findings are (1) Field-based techniques (e.g., allometric equations, quadrat sampling) provide reliable and site-specific estimates but are labor-intensive and limited in scalability. (2) Remote sensing methods (LiDAR, UAVs, multispectral and radar imagery) enable large-scale and repeat assessments, though they require extensive calibration and investment. (3) Machine learning and hybrid approaches enhance prediction accuracy by integrating multi-source data, but their success depends on data availability and methodological harmonization. This review identifies opportunities for integrating field and remote sensing data with machine learning to strengthen biomass monitoring. Establishing a national biomass inventory, supported by robust policy frameworks, is critical to align Kenya’s forest management with global climate and biodiversity goals. Full article
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