Topic Editors

Department of Ecology, School of Plant Protection, Yangzhou University, Yangzhou 225009, China
Prof. Dr. Fei Zhang
College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, China
GeoInformatic Unit, Geography Section, School of Humanities, Universiti Sains Malaysia, Penang, Malaysia
Dr. Kwok Pan Chun
CATE School of Architecture and Environment, University of the West of England, Bristol BS16 1QY, UK

Climate Change Impacts and Adaptation: Interdisciplinary Perspectives

Abstract submission deadline
31 October 2024
Manuscript submission deadline
31 December 2024
Viewed by
7004

Topic Information

Dear Colleagues,

With the increasing concentration of greenhouse gases in the atmosphere, climate change is now an indisputable fact and poses great challenges to the environment, economies, and communities. These challenges are further compounded by inaction, which can lead to severe impacts on human health, food security, and global stability. Fortunately, a number of studies have been carried out with a focus on acquiring knowledge of climate change and its impacts on the ecosystem and national sectors such as agriculture, forestry, water resources, etc. However, there are still many uncertainties regarding impact assessment results and practical adaptive measures because of limited data and methodologies and the scale of such studies. Therefore, case studies should be strengthened and broadened to reduce these uncertainties and develop practical adaptive measures to cope with climate change.

This Topic seeks to bring together interdisciplinary perspectives to address the ever-expanding importance of climate change impacts and adaptation. Despite a broad range of research undertaken by different countries, organizations, and industries to address climate change, a great deal of very important work remains to be completed to effectively assess the impacts of climate change and to understand the extent to which adaptation measures can reduce the negative impacts of climate change.

For this Topic, we warmly invite scientists working in climatology, ecology, geography, remote sensing and GIS, environmental science, and social science to contribute novel theories, observations, and modeling studies on climate change impacts and adaptation across different time scales (historical to future) and spatial scales (regional to global). Contributions can include but are not limited to the following: observation-based regional climate change analysis, the detection and attribution of regional climate change, the measurement and modeling of land surface–atmosphere interaction, the impacts and risks of climate change on different regions (or sectors), meteorological disaster risk management, climate change and sustainable development, international climate governance, etc.

Dr. Cheng Li
Prof. Dr. Fei Zhang
Dr. Mou Leong Tan
Dr. Kwok Pan Chun
Topic Editors

Keywords

  • regional climate change
  • land–atmosphere interactions
  • greenhouse gas emissions
  • climate and vegetation relationships
  • impacts of climate change
  • risk management
  • climate change adaptation
  • climate governance
  • remote sensing and GIS
  • machine learning and numerical modeling methods

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Agronomy
agronomy
3.7 5.2 2011 15.8 Days CHF 2600 Submit
Applied Sciences
applsci
2.7 4.5 2011 16.9 Days CHF 2400 Submit
Climate
climate
3.7 5.2 2013 19.7 Days CHF 1800 Submit
Forests
forests
2.9 4.5 2010 16.9 Days CHF 2600 Submit
Remote Sensing
remotesensing
5.0 7.9 2009 23 Days CHF 2700 Submit
Sustainability
sustainability
3.9 5.8 2009 18.8 Days CHF 2400 Submit

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Published Papers (10 papers)

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27 pages, 8244 KiB  
Article
Intra-Annual Cumulative Effects and Mechanisms of Climatic Factors on Global Vegetation Biomes’ Growth
Remote Sens. 2024, 16(5), 779; https://doi.org/10.3390/rs16050779 - 23 Feb 2024
Viewed by 231
Abstract
Previous studies have shown that climate change has significant cumulative effects on vegetation growth. However, there remains a gap in understanding the characteristics of cumulative climatic effects on different vegetation types and the underlying driving mechanisms. In this study, using the normalized difference [...] Read more.
Previous studies have shown that climate change has significant cumulative effects on vegetation growth. However, there remains a gap in understanding the characteristics of cumulative climatic effects on different vegetation types and the underlying driving mechanisms. In this study, using the normalized difference vegetation index data from 1982 to 2015, along with accumulated temperature, precipitation, and solar radiation data, we quantitatively investigated the intra-annual cumulative effects of climatic factors on global vegetation biomes across climatic zones. We also explored the underlying driving mechanisms. The results indicate that precipitation has a longer intra-annual cumulative effect on vegetation, with effects lasting up to 12 months for large percentages of most vegetation biomes. The cumulative effect of solar radiation is mostly concentrated within 0–6 months. Temperature has a shorter cumulative effect, with no significant cumulative effect of temperature on large percentages of tree-type vegetation. Compared to other vegetation types, evergreen broadleaf forests, close shrublands, open shrublands, savannas, and woody savannas exhibit more complex cumulative climatic effects. Each vegetation type shows a weak-to-moderate correlation with accumulated precipitation while exhibiting strong-to-extremely-strong positive correlations with accumulated temperature and accumulated solar radiation. The climate-induced regulations of water, heat, and nutrient, as well as the intrinsic mechanisms of vegetation’s tolerance, resistance, and adaptation to climate change, account for the significant heterogeneity of cumulative climatic effects across vegetation biomes in different climatic zones. This study contributes to enriching the theoretical understanding of the relationship between vegetation growth and climate change. It also offers crucial theoretical support for developing climate change adaptation strategies and improving future “vegetation-climate” models. Full article
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15 pages, 754 KiB  
Article
Environmental Management of Ecuador’s Business Sector in the Fight against Climate Change
Sustainability 2024, 16(5), 1837; https://doi.org/10.3390/su16051837 - 23 Feb 2024
Viewed by 204
Abstract
The private sector is part of the United Nations Global Compact, which promotes the voluntary participation of organizations to implement environmental care strategies. The purpose of this article is to examine the performance of Ecuadorian companies in regard to environmental management, especially in [...] Read more.
The private sector is part of the United Nations Global Compact, which promotes the voluntary participation of organizations to implement environmental care strategies. The purpose of this article is to examine the performance of Ecuadorian companies in regard to environmental management, especially in the fight against climate change, considering the economic sectors (manufacturing, mining, commerce, construction and services). Figures from the National Institute of Statistics and the Census of Ecuador (2020) are used, including descriptive statistics and cross-tabulations with Cramer’s V index. The results show that approximately 5% of companies had the ISO 14001:2015 certification. In the seven actions against climate change considered, the proportion of companies that did not consider them to be current expenses predominated. Cramer’s V index, for associating the economic sector and the environmental spend, revealed that certain economic sectors (manufacturing and mining) are contributing significantly to environmental management spending in the areas of air, soil, wastewater and waste treatment, while no economic sector dominates the others in areas such as radiation treatment, the use of mineral or energy resources and water resources. Full article
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20 pages, 12932 KiB  
Article
Enhancing Maize Yield Simulations in Regional China Using Machine Learning and Multi-Data Resources
Remote Sens. 2024, 16(4), 701; https://doi.org/10.3390/rs16040701 - 16 Feb 2024
Viewed by 386
Abstract
Improved agricultural production systems, together with increased grain yield, are essential to feed the growing global population in the 21st century. Global gridded crop models (GGCMs) have been extensively used to assess crop production and yield simulation on a large geographical scale. However, [...] Read more.
Improved agricultural production systems, together with increased grain yield, are essential to feed the growing global population in the 21st century. Global gridded crop models (GGCMs) have been extensively used to assess crop production and yield simulation on a large geographical scale. However, GGCMs are less effective when they are used on a finer scale, significantly limiting the precision in capturing the yearly maize yield. To address this issue, we propose a relatively more advanced approach that downsizes GGCMs by combining machine learning and crop modeling to enhance the accuracy of maize yield simulations on a regional scale. In this study, we combined the random forest algorithm with multiple data sources, trained the algorithm on low-resolution maize yield simulations from GGCMs, and applied it to a finer spatial resolution on a regional scale in China. We evaluated the performance of the eight GGCMs by utilizing a total of 1046 county-level maize yield data available over a 30-year period (1980–2010). Our findings reveal that the downscaled models created for maize yield simulations exhibited a remarkable level of accuracy (R2 ≥ 0.9, MAE < 0.5 t/ha, RMSE < 0.75 t/ha). The original GGCMs performed poorly in simulating county-level maize yields in China, and the improved GGCMs in our study captured an additional 17% variability in the county-level maize yields in China. Additionally, by optimizing nitrogen management strategies, we identified an average maize yield gap at the county level in China ranging from 0.47 to 1.82 t/ha, with the south maize region exhibiting the highest yield gap. Our study demonstrates the high effectiveness of machine learning methods for the spatial downscaling of crop models, significantly improving GGCMs’ performance in county-level maize yield simulations. Full article
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18 pages, 3401 KiB  
Article
Visualising the Relevance of Climate Change for Spatial Planning by the Example of Serbia
Appl. Sci. 2024, 14(4), 1530; https://doi.org/10.3390/app14041530 - 14 Feb 2024
Viewed by 324
Abstract
After decades of rising awareness and undertaken actions, climate change is still one of several focal global challenges. Additionally, the latest report by researchers at the International Panel for Climate Change indicates that the crisis has deepened. With its comprehensive nature, spatial planning [...] Read more.
After decades of rising awareness and undertaken actions, climate change is still one of several focal global challenges. Additionally, the latest report by researchers at the International Panel for Climate Change indicates that the crisis has deepened. With its comprehensive nature, spatial planning is one of the management tools responsible for dealing with climate change and combating its effects. Land use definition is the foundation on which we build mitigation and adaptation systems. It is a complex process that involves (or should involve) a range of stakeholders—experts, politicians, the civil sector, and citizens—in which the clear transmission of messages to stakeholders regarding the state of the art and planned actions is significant. The use of visualisation tools is one of the important ways to achieve this. This research aims to present a set of visualisation tools, applying them in analysis and decision making in the field of spatial planning with regard to climate change. We combined content analysis, colour-graded classification, and the spider method applied to the example of Serbia. The results showed that application of the suggested visualisation methods in combination with regular planning tools (maps) facilitates an understanding of the problem and its presentation to other stakeholders. In the case of Serbia, visualisation tools have shown that adaptation measures prevail over mitigation measures and that the effects of climate change addressed in spatial-planning documents do not significantly match the most challenging effects as perceived from the citizens’ perspective. These are aspects that should be corrected in the next generation of planning documents. The suggested visualisation tools are replicable, with slight adjustments to a specific case, to any other region in the world. Full article
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12 pages, 265 KiB  
Article
Addressing the Climate Change Adaptation Gap: Key Themes and Future Directions
Climate 2024, 12(2), 24; https://doi.org/10.3390/cli12020024 - 08 Feb 2024
Viewed by 1278
Abstract
Climate change adaptation is a critical response to the challenges posed by climate change and is important for building resilience. Progress in adaptation efforts has been made globally, nationally, and locally through international agreements, national plans, and community-based initiatives. However, significant gaps exist [...] Read more.
Climate change adaptation is a critical response to the challenges posed by climate change and is important for building resilience. Progress in adaptation efforts has been made globally, nationally, and locally through international agreements, national plans, and community-based initiatives. However, significant gaps exist in knowledge, capacity, and finance. The Adaptation Gap Report 2023, published by the United Nations Environment Programme (UNEP), examines the status of climate change adaptation efforts globally. The report highlights the widening adaptation finance gap and the deepening climate crisis. We analyse the key themes of the report and incorporate an analysis of the wider literature and insights from COP28 to substantiate key points and identify gaps where more work is needed to develop an understanding of climate change adaptation. This paper focuses on the underfinanced and underprepared state of global climate change adaptation efforts, the widening adaptation finance gap, slow progress in adaptation, gender equality and social inclusion issues, and challenges in addressing loss and damage. We provide a way forward for climate change adaptation and offer recommendations for future actions. Full article
18 pages, 4216 KiB  
Article
The Variation Characteristics of Stratospheric Circulation under the Interdecadal Variability of Antarctic Total Column Ozone in Early Austral Spring
Remote Sens. 2024, 16(4), 619; https://doi.org/10.3390/rs16040619 - 07 Feb 2024
Viewed by 374
Abstract
Antarctic Total Column Ozone (TCO) gradually began to recover around 2000, and a large number of studies have pointed out that the recovery of the Antarctic TCO is most significant in the austral early spring (September). Based on the Bodeker Scientific Filled Total [...] Read more.
Antarctic Total Column Ozone (TCO) gradually began to recover around 2000, and a large number of studies have pointed out that the recovery of the Antarctic TCO is most significant in the austral early spring (September). Based on the Bodeker Scientific Filled Total Column Ozone and ERA5 reanalysis dataset covering 1979–2019, the variation characteristics of the Antarctic TCO and stratospheric circulation for the TCO ‘depletion’ period (1979–1999) and the ‘recovery’ period (2000–2019) are analyzed in September. Results show that: (1) Stratospheric elements significantly related to the TCO have corresponding changes during the two eras. (2) The interannual variability of the TCO and the above-mentioned stratospheric circulation elements in the recovery period are stronger than those in the depletion period. (3) Compared with the depletion period, due to the stronger amplitude of the planetary wave 1, stronger Eliassen–Palm (EP) flux corresponds to EP flux convergence, larger negative eddy heat flux, and positive eddy momentum flux in the stratosphere during the recovery period. The polar temperature rises in the lower and middle stratosphere and the polar vortex weakens in the middle and upper stratosphere, accompanied by the diminished area of PSC. This contributes to the understanding of Antarctic ozone recovery. Full article
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26 pages, 10782 KiB  
Article
Adaptation of Tree Species in the Greater Khingan Range under Climate Change: Ecological Strategy Differences between Larix gmelinii and Quercus mongolica
Forests 2024, 15(2), 283; https://doi.org/10.3390/f15020283 - 02 Feb 2024
Viewed by 583
Abstract
Global warming significantly affects forest ecosystems in the Northern Hemisphere’s mid-to-high latitudes, altering tree growth, productivity, and spatial distribution. Additionally, spatial and temporal heterogeneity exists in the responses of different tree species to climate change. This research focuses on two key species in [...] Read more.
Global warming significantly affects forest ecosystems in the Northern Hemisphere’s mid-to-high latitudes, altering tree growth, productivity, and spatial distribution. Additionally, spatial and temporal heterogeneity exists in the responses of different tree species to climate change. This research focuses on two key species in China’s Greater Khingan Range: Larix gmelinii (Rupr.) Kuzen. (Pinaceae) and Quercus mongolica Fisch. ex Ledeb. (Fagaceae). We utilized a Maxent model optimized by the kuenm R package to predict the species’ potential habitats under various future climate scenarios (2050s and 2070s) considering three distinct Shared Socioeconomic Pathways: SSP1-2.6, SSP2-4.5, and SSP5-8.5. We analyzed 313 distribution records and 15 environmental variables and employed geospatial analysis to assess habitat requirements and migration strategies. The Maxent model demonstrated high predictive accuracy, with Area Under the Curve (AUC) values of 0.921 for Quercus mongolica and 0.985 for Larix gmelinii. The high accuracy was achieved by adjusting the regularization multipliers and feature combinations. Key factors influencing the habitat of Larix gmelinii included the mean temperature of the coldest season (BIO11), mean temperature of the warmest season (BIO10), and precipitation of the driest quarter (BIO17). Conversely, Quercus mongolica’s habitat suitability was largely affected by annual mean temperature (BIO1), elevation, and annual precipitation (BIO12). These results indicate divergent adaptive responses to climate change. Quercus mongolica’s habitable area generally increased in all scenarios, especially under SSP5-8.5, whereas Larix gmelinii experienced more complex habitat changes. Both species’ distribution centroids are expected to shift northwestward. Our study provides insights into the divergent responses of coniferous and broadleaf species in the Greater Khingan Range to climate change, contributing scientific information vital to conserving and managing the area’s forest ecosystems. Full article
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22 pages, 3277 KiB  
Review
Net Zero Dairy Farming—Advancing Climate Goals with Big Data and Artificial Intelligence
Climate 2024, 12(2), 15; https://doi.org/10.3390/cli12020015 - 25 Jan 2024
Viewed by 1495
Abstract
This paper explores the transformative potential of Big Data and Artificial Intelligence (AI) in propelling the dairy industry toward net zero emissions, a critical objective in the global fight against climate change. Employing the Canadian dairy sector as a case study, the study [...] Read more.
This paper explores the transformative potential of Big Data and Artificial Intelligence (AI) in propelling the dairy industry toward net zero emissions, a critical objective in the global fight against climate change. Employing the Canadian dairy sector as a case study, the study extrapolates its findings to demonstrate the global applicability of these technologies in enhancing environmental sustainability across the agricultural spectrum. We begin by delineating the environmental challenges confronting the dairy industry worldwide, with an emphasis on greenhouse gas (GHG) emissions, including methane from enteric fermentation and nitrous oxide from manure management. The pressing need for innovative approaches in light of the accelerating climate crisis forms the crux of our argument. Our analysis delves into the role of Big Data and AI in revolutionizing emission management in dairy farming. This includes applications in optimizing feed efficiency, refining manure management, and improving energy utilization. Technological solutions such as predictive analytics for feed optimization, AI in herd health management, and sensor networks for real-time monitoring are thoroughly examined. Crucially, the paper addresses the wider implications of integrating these technologies in dairy farming. We discuss the development of benchmarking standards for emissions, the importance of data privacy, and the essential role of policy in promoting sustainable practices. These aspects are vital in supporting the adoption of technology, ensuring ethical use, and aligning with international climate commitments. Concluding, our comprehensive study not only suggests a pathway for the dairy industry towards environmental sustainability but also provides insights into the role of digital technologies in broader agricultural practices, aligning with global environmental sustainability efforts. Full article
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22 pages, 2926 KiB  
Review
Meta-Analysis of Life Cycle Assessment Studies for Polyethylene Terephthalate Water Bottle System
Sustainability 2024, 16(2), 535; https://doi.org/10.3390/su16020535 - 08 Jan 2024
Viewed by 723
Abstract
The life cycle assessment (LCA) serves as a crucial tool for assessing the environmental impact of products, with recent emphasis on polyethylene terephthalate (PET) bottles. Our meta-analytical review of 14 LCA research papers (2010–2022) on PET bottles, aligned with PRISMA guidelines, spans six [...] Read more.
The life cycle assessment (LCA) serves as a crucial tool for assessing the environmental impact of products, with recent emphasis on polyethylene terephthalate (PET) bottles. Our meta-analytical review of 14 LCA research papers (2010–2022) on PET bottles, aligned with PRISMA guidelines, spans six phases: raw material production (MP), bottle production (BP), distribution and transportation (DT), collection and transport (CT), waste management (WM), and environmental benefits (EB). Utilizing the global warming potential (GWP) as the indicator, our study harmonized data into a consistent functional unit, revealing an average emission of 5.1 kg CO2 equivalent per 1 kg of PET bottles. Major contributors to global warming were identified across the MP, BP, and DT phases. While the MP and BP phases exhibited low variability due to uniform processes, the CT, WM, and EB phases displayed higher variability due to scenario considerations. A comparison with Korean environmental product declaration data affirmed the methodology’s practical utility. Our approach offers potential applicability in diverse product category assessments, emphasizing its relevance for informed decision-making in sustainable product development. Full article
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22 pages, 5698 KiB  
Article
Estimation of the Short-Term Impact of Climate-Change-Related Factors on Wood Supply in Poland in 2023–2025
Forests 2024, 15(1), 108; https://doi.org/10.3390/f15010108 - 05 Jan 2024
Viewed by 652
Abstract
In this study, we analyzed in situ data from the years 2018–2022 encompassing entire forest plantations in Poland. Based on data regarding stand density and the occurrence of fungal, water-related, climate-related, fire, and insect factors that may intensify with climate changes, we determined [...] Read more.
In this study, we analyzed in situ data from the years 2018–2022 encompassing entire forest plantations in Poland. Based on data regarding stand density and the occurrence of fungal, water-related, climate-related, fire, and insect factors that may intensify with climate changes, we determined the correlation between their occurrence and the decline in wood increments for six tree species: pine, birch, oak, spruce, beech, and alder. Subsequently, we identified age intervals in which the species–factor interaction exhibited statistically significant effects. Next, we developed neural network models for short-term wood increment predictions. Utilizing these models, we estimated a reduction in wood supply harvested in accordance with the plans for the years 2023–2025 assuming a tenfold greater intensity of factors than in 2022. Findings indicate: birch: water-related factors may reduce wood production by 0.1%–0.2%. This aligns with previous research linking drought to birch wood decline, highlighting its sensitivity to water-related issues. Oak: fungal and insect factors could decrease wood production by up to 0.1%. Prior studies emphasize the significant influence of fungal diseases on oak health and regeneration, as well as the impact of insect infestation on wood production. Alder: water-related factors may lead to a slight reduction in wood production, approximately 0.02%. The impact is significant within specific age ranges, indicating potential effects on harvesting. Pine: water- and climate-related factors may result in up to a 0.05% reduction in wood production. Pine, a key forest-forming species in Poland, is notably sensitive to these factors, especially as it nears harvesting age. Spruce: insects, fungi, and climate-related factors could lead to a reduction in wood production of up to 0.2%–0.3%. Analyses demonstrate sensitivity, resulting in a noticeable growth differential compared to the typical rate. Short-term predictions based on neural networks were developed, acknowledging their suitability for short-term forecasts due to uncertainties regarding long-term factor impacts. Additionally, our study discussed modeling wood increments in divisions well below the harvesting time, emphasizing that the influence of current and 2023–2025 factors on wood increments and supply may only manifest several decades from now. These results imply important indications for the economic and financial performance of the wood industry. Full article
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