Climate Change Impacts and Adaptation: Interdisciplinary Perspectives

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
ISPRS International Journal of Geo-Information ijgi	3.4	6.2	2012	35.5 Days	CHF 1700	Submit

24 pages, 1611 KiB

Open AccessArticle

The Effectiveness of Climate Adaptation Finance and Readiness on Vulnerability in African Economies

by Purity Maina and Anett Parádi-Dolgos

Climate 2024, 12(5), 59; https://doi.org/10.3390/cli12050059 - 24 Apr 2024

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Addressing climate vulnerability remains a priority for economies globally. This study used the panel-corrected standard error (PCSE) methodology to investigate the impact of adaptation financing on climate vulnerability. This analysis examined 52 African countries from 2012 to 2021 while considering their climate adaptation [...] Read more.

Addressing climate vulnerability remains a priority for economies globally. This study used the panel-corrected standard error (PCSE) methodology to investigate the impact of adaptation financing on climate vulnerability. This analysis examined 52 African countries from 2012 to 2021 while considering their climate adaptation readiness. The impact was also assessed based on the Human Development Index (HDI) categories to reflect different levels of development. The findings showed that adaptation finance considerably influenced climate vulnerability reduction in Africa, particularly in nations with a moderate HDI. However, most countries still need higher levels of adaptation financing, resulting in a small impact on vulnerability reduction. Furthermore, the impact of readiness measures differed by HDI category. Economic and social climate readiness strongly impacted climate vulnerability in high-HDI nations, but governance preparedness was more critical in low-HDI countries. Based on the empirical facts, two policy proposals emerge. First, it is critical to reconsider the distribution of adaptation financing to reduce disparities and effectively alleviate climate vulnerability. Moreover, African economies should consider implementing innovative localized financing mechanisms to mobilize extra adaptation finance. Second, African governments should customize climate readiness interventions based on their HDI levels to improve the achievement of a positive impact on climate vulnerability. Full article

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

15 pages, 10305 KiB

Open AccessArticle

Climate Change Impact on the Distribution of Forest Species in the Brazilian Amazon

by Ingrid Lana Lima de Morais, Alexandra Amaro de Lima, Ivinne Nara Lobato dos Santos, Carlos Meneses, Rogério Freire da Silva, Ricardo Lopes, Santiago Linorio Ferreyra Ramos, Ananda Virginia de Aguiar, Marcos Silveira Wrege and Maria Teresa Gomes Lopes

Sustainability 2024, 16(8), 3458; https://doi.org/10.3390/su16083458 - 20 Apr 2024

Viewed by 556

Abstract

Studies using ecological niche models highlight the vulnerability of forest species to climate change. This work aimed to analyze the distribution of timber species Aspidosperma desmanthum, Cariniana micranta, Clarisia racemosa, Couratari oblongifolia, and Vouchysia guianensis, which are targets [...] Read more.

Studies using ecological niche models highlight the vulnerability of forest species to climate change. This work aimed to analyze the distribution of timber species Aspidosperma desmanthum, Cariniana micranta, Clarisia racemosa, Couratari oblongifolia, and Vouchysia guianensis, which are targets of deforestation, to predict the impacts of climate change and identify areas for their conservation in the Amazon. For this purpose, 37 environmental variables were used, including climatic and edaphic factors. The models were fitted using five algorithms, and their performance was evaluated by the metrics Area Under the Curve (AUC), True Skill Statistic, and Sorensen Index. The deforestation analysis was conducted using data accumulated over a period of 14 years. The study indicated that under the most pessimistic predictions, considering continued high emissions of greenhouse gases (GHGs) from the use of fossil fuels, SSP5–8.5, potential habitat loss for the studied species was more significant. Analyses of the species show that the Western Amazon has a greater climatic suitability area for the conservation of its genetic resources. Further study of the accumulated deforestation over 14 years showed a reduction in area for all species. Therefore, in situ conservation policies and deforestation reduction are recommended for the perpetuation of the analyzed forest species. Full article

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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15 pages, 5346 KiB

Open AccessArticle

Spatial Heterogeneity in the Response of Winter Wheat Yield to Meteorological Dryness/Wetness Variations in Henan Province, China

by Cheng Li, Yuli Gu, Hui Xu, Jin Huang, Bo Liu, Kwok Pan Chun and Thanti Octavianti

Agronomy 2024, 14(4), 817; https://doi.org/10.3390/agronomy14040817 - 14 Apr 2024

Viewed by 527

Abstract

Knowledge of the responses of winter wheat yield to meteorological dryness/wetness variations is crucial for reducing yield losses in Henan province, China’s largest winter wheat production region, under the background of climate change. Data on climate, yield and atmospheric circulation indices were collected [...] Read more.

Knowledge of the responses of winter wheat yield to meteorological dryness/wetness variations is crucial for reducing yield losses in Henan province, China’s largest winter wheat production region, under the background of climate change. Data on climate, yield and atmospheric circulation indices were collected from 1987 to 2017, and monthly self-calibrating Palmer drought severity index (sc-PDSI) values were calculated during the winter wheat growing season. The main results were as follows: (1) Henan could be partitioned into four sub-regions, namely, western, central-western, central-northern and eastern regions, based on the evolution characteristics of the time series of winter wheat yield in 17 cities during the period of 1988–2017. Among them, winter wheat yield was high and stable in the central-northern and eastern regions, with a remarkable increasing trend (p < 0.05). (2) The sc-PDSI in February had significantly positive impacts on climate-driven winter wheat yield in the western and central-western regions (p < 0.05), while the sc-PDSI in December and the sc-PDSI in May had significantly negative impacts on climate-driven winter wheat yield in the central-northern and eastern regions, respectively (p < 0.05). (3) There were time-lag relationships between the sc-PDSI for a specific month and the atmospheric circulation indices in the four sub-regions. Furthermore, we constructed multifactorial models based on selected atmospheric circulation indices, and they had the ability to simulate the sc-PDSI for a specific month in the four sub-regions. These findings will provide scientific references for meteorological dryness/wetness monitoring and risk assessments of winter wheat production. Full article

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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18 pages, 48964 KiB

Open AccessArticle

Exploring the Spatiotemporal Alterations in China’s GPP Based on the DTEC Model

by Jie Peng, Yayong Xue, Naiqing Pan, Yuan Zhang, Haibin Liang and Fei Zhang

Remote Sens. 2024, 16(8), 1361; https://doi.org/10.3390/rs16081361 - 12 Apr 2024

Viewed by 354

Abstract

Gross primary productivity (GPP) is a reliable measure of the carbon sink potential of terrestrial ecosystems and is an essential element of terrestrial carbon cycle research. This study employs the diffuse fraction-based two-leaf light-use efficiency (DTEC) model to imitate China’s monthly GPP from [...] Read more.

Gross primary productivity (GPP) is a reliable measure of the carbon sink potential of terrestrial ecosystems and is an essential element of terrestrial carbon cycle research. This study employs the diffuse fraction-based two-leaf light-use efficiency (DTEC) model to imitate China’s monthly GPP from 2001 to 2020. We studied the trend of GPP, investigated its relationship with climatic factors, and separated the contributions of climate change and human activities. The findings showed that the DTEC model was widely applicable in China. During the study period, China’s average GPP increased significantly, by 9.77 g C m⁻² yr⁻¹ (p < 0.001). The detrimental effect of aerosol optical depth (AOD) on GPP was more widespread than that of total precipitation, temperature, and solar radiation. Areas that benefited from AOD, such as Northwest China, experienced significant increases in GPP. Climate change and human activities had a primary and positive influence on GPP during the study period, accounting for 28% and 72% of the increase, respectively. Human activities, particularly ecological restoration projects and the adoption of advanced agricultural technologies, played a significant role in China’s GPP growth. China’s afforestation plan was particularly notable, with the GPP increasing in afforestation areas at a rate greater than 10 g C m⁻² yr⁻¹. This research provides a theoretical foundation for the long-term management of China’s terrestrial ecosystems and helps develop adaptive ecological restoration tactics. Full article

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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52 pages, 39816 KiB

Open AccessArticle

Current Situation of Traditional Architecture Located inside Cultural Mayan Heritage Spaces in Remote Villages of Guatemala: Case of the Black Salt Kitchens

by Luis Pablo Yon Secaida, Suguru Mori and Rie Nomura

Sustainability 2024, 16(8), 3194; https://doi.org/10.3390/su16083194 - 11 Apr 2024

Viewed by 359

Abstract

In the town of Sacapulas, located in the mountainous country of Guatemala, there is a constant risk of natural disasters. Floods and landslides occur frequently, resulting in the loss of human lives and cultural aspects. Important to the region, the creation of the [...] Read more.

In the town of Sacapulas, located in the mountainous country of Guatemala, there is a constant risk of natural disasters. Floods and landslides occur frequently, resulting in the loss of human lives and cultural aspects. Important to the region, the creation of the black salt is most affected. This resource has been created since the time of the Mayans on the salt beach surrounding the town. However, from the 1940s onwards, this industry has shrunk. As a result, architectural expressions known as “salt kitchens” have almost disappeared, and there is no information on the subject available. By employing interviews, area survey, and GPS mapping, it was discovered that the location of the salt kitchens is determined by the shape of the beach. However, only one third of the beach area is accessible up to this day. It was discovered that the destruction of the salt kitchens is due to natural elements as well as owners reusing the land for other economically viable functions. To preserve their existence, the first plans of the salt kitchens were created, and will help future researchers if necessary. Full article

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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15 pages, 9137 KiB

Open AccessArticle

Predicting the Potential Geographic Distribution of Invasive Freshwater Apple Snail Pomacea canaliculate (Lamarck, 1819) under Climate Change Based on Biomod2

by Tao Wang, Tingjia Zhang, Weibin An, Zailing Wang and Chuanren Li

Agronomy 2024, 14(4), 650; https://doi.org/10.3390/agronomy14040650 - 23 Mar 2024

Viewed by 505

Abstract

Pomacea canaliculata is widely distributed in the Chinese provinces south of the Yangtze River, causing serious damage to aquatic ecosystems, rice cultivation, and human health. Predicting the potential geographic distributions (PGDs) of P. canaliculata under current and future climate conditions in China is [...] Read more.

Pomacea canaliculata is widely distributed in the Chinese provinces south of the Yangtze River, causing serious damage to aquatic ecosystems, rice cultivation, and human health. Predicting the potential geographic distributions (PGDs) of P. canaliculata under current and future climate conditions in China is crucial for developing effective early warning measures and facilitating long-term monitoring. In this study, we screened various species distribution models (SDMs), including CTA, GBM, GAM, RF, and XGBOOST, to construct an ensemble model (EM) and then predict suitable habitats for P. canaliculata under current and future climate scenarios (SSP1-26, SSP2-45, SSP3-70, SSP5-85). The EM (AUC = 0.99, TSS = 0.96) yielded predictions that were more precise than those from the individual models. The Annual Mean Temperature (Bio1) and Precipitation of the Warmest Quarter (Bio18) are the most significant environmental variables affecting the PGDs of P. canaliculata. Under current climate conditions, the highly suitable habitats for P. canaliculata are primarily located south of the Yangtze River, collectively accounting for 17.66% of the nation’s total area. Unsuitable habitats predominate in higher-latitude regions, collectively covering 66.79% of China’s total land area. In future climate scenarios, the total number of suitable habitats for P. canaliculata is projected to expand into higher latitude regions, especially under SSP3-70 and SSP5-85 climate conditions. The 4.1 °C contour of Bio1 and the 366 mm contour of Bio18 determine the northernmost geographical distribution of P. canaliculata. Climate change is likely to increase the risk of P. canaliculata expanding into higher latitudes. Full article

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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19 pages, 3051 KiB

Open AccessArticle

Harmonizing the Development of Local Socioeconomic Scenarios: A Participatory Downscaling Approach Applied in Four European Case Studies

by Athanasios Thomas Vafeidis, Lena Reimann, Gerald Jan Ellen, Gunnel Goransson, Gerben Koers, Lisa Van Well, Bente Vollstedt, Maureen Tsakiris and Amy Oen

Sustainability 2024, 16(6), 2578; https://doi.org/10.3390/su16062578 - 21 Mar 2024

Viewed by 486

Abstract

Scenario analysis is a widely employed method for addressing uncertainties when assessing the physical and socio-economic impacts of climate change. Global scenarios have been extensively used in this context. However, these scenarios are in most cases not suitable for supporting local analyses. On [...] Read more.

Scenario analysis is a widely employed method for addressing uncertainties when assessing the physical and socio-economic impacts of climate change. Global scenarios have been extensively used in this context. However, these scenarios are in most cases not suitable for supporting local analyses. On the other hand, locally developed scenarios may lack the global context, thus having limited comparability with or transferability to other locations. The Shared Socioeconomic Pathways (SSP), which have been primarily developed for climate impact research, provide the possibility to extend the existing global narratives and adapt them to local characteristics in order to develop locally relevant scenarios. Here, we propose a methodological framework for producing harmonized scenarios across different case studies. This framework was developed in the EVOKED project and combines elements of top-down and bottom-up approaches to develop local scenarios for four regions in northern Europe. We employ the SSP as boundary conditions and, in cooperation with stakeholders from these four regions, develop local scenarios for a range of SSP. The developed sets of scenarios are consistently informed by global developments and are therefore comparable with other downscaled scenarios developed in different regions. At the same time, they have been based on local participatory processes, thus being locally credible and relevant to the needs of stakeholders. The local scenarios constitute a climate service per se as they can raise stakeholder awareness of the processes that will drive risk, exposure, and adaptive capacity in the future and inform discussions on mitigation strategies and adaptation pathways. Full article

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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17 pages, 3915 KiB

Open AccessArticle

Developing a New ANN Model to Estimate Daily Actual Evapotranspiration Using Limited Climatic Data and Remote Sensing Techniques for Sustainable Water Management

by Halil Karahan, Mahmut Cetin, Muge Erkan Can and Omar Alsenjar

Sustainability 2024, 16(6), 2481; https://doi.org/10.3390/su16062481 - 17 Mar 2024

Viewed by 842

Abstract

Accurate estimations of actual evapotranspiration (ETa) are essential to various environmental issues. Artificial intelligence-based models are a promising alternative to the most common direct ETa estimation techniques and indirect methods by remote sensing (RS)-based surface energy balance models. Artificial Neural Networks (ANNs) are [...] Read more.

Accurate estimations of actual evapotranspiration (ETa) are essential to various environmental issues. Artificial intelligence-based models are a promising alternative to the most common direct ETa estimation techniques and indirect methods by remote sensing (RS)-based surface energy balance models. Artificial Neural Networks (ANNs) are proven to be suitable for predicting reference evapotranspiration (ETo) and ETa based on RS data. This study aims to develop a methodology based on ANNs for estimating daily ETa values using NDVI and land surface temperature, coupled with limited site-specific climatic variables in a large irrigation catchment. The ANN model has been applied to the two different scenarios. Data from only the 38 days of satellite overpass dates was selected in Scenario I, while in Scenario II all datasets, i.e., the 769-day data were used. An irrigation scheme, located in the Mediterranean region of Turkiye, was selected, and a total of 38 Landsat images and local climatic data collected in 2021 and 2022 were used in the ANN model. The ETa results by the ANN model for Scenarios I and II showed that the R² values for training (0.79 and 0.86), testing (0.75 and 0.81), and the entire dataset (0.76 and 0.84) were all remarkably high. Moreover, the results of the new ANN model in two scenarios showed an acceptable agreement with ETa-METRIC values. The proposed ANN model demonstrated the potential for obtaining daily ETa using limited climatic data and RS imagery. As a result, the suggested ANN model for daily ETa computation offers a trustworthy way to determine crop water usage in real time for sustainable water management in agriculture. It may also be used to assess how crop evapotranspiration in drought-prone areas will be affected by climate change in the 21st century. Full article

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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19 pages, 2786 KiB

Open AccessArticle

Understanding Constraints and Enablers of Climate Risk Management Strategies: Evidence from Smallholder Dairy Farmers in Regional South India

by Anupama Shantharaju, Md Aminul Islam, Jarrod M. Kath, Shahbaz Mushtaq, Arun Muniyappa and Lila Singh-Peterson

Sustainability 2024, 16(5), 2018; https://doi.org/10.3390/su16052018 - 29 Feb 2024

Viewed by 720

Abstract

The adoption of effective coping strategies is crucial for successful adaptation to the impacts of climate change in the dairy sector. However, little attention has been paid to understanding the perceived constraints and motivations toward such strategies. A survey was conducted among 104 [...] Read more.

The adoption of effective coping strategies is crucial for successful adaptation to the impacts of climate change in the dairy sector. However, little attention has been paid to understanding the perceived constraints and motivations toward such strategies. A survey was conducted among 104 dairy farmers from three semi-arid regions of South India. The aim of the survey was to explore the dairy farmers’ perception of climate risk, how it impacts their dairy farming system, the coping strategies they employ, and the barriers they face when implementing these strategies. The survey also investigated the factors that facilitate the adoption of adaptation measures. The results indicate dairy farmers in the region perceive drought, pests and diseases, and high temperatures as the major risks associated with climate change, which has resulted in decreased dairy income, animal health problems, reduced fertility, and food intake problems for their cattle. In response to climate variability, dairy farmers have adopted various coping strategies. The most important strategies include buying livestock insurance, keeping low debt obligations, and growing drought-tolerant grass varieties. However, most farmers face significant constraints in adopting these and other strategies including a lack of climate forecast data, the high cost of adaptation activities, and weak institutional support. On the other hand, the key enabling factors that support the adoption of these strategies include milk production security, suitable feed growing conditions, and family interest. Most importantly, the study found that certain factors such as age, education, number of earning family members, annual milk production, monthly cattle expenses, and landholdings significantly influenced dairy farmers’ strategies for adapting to climate change. The study recommends that providing timely climate forecasts, implementing improved policies such as vaccination and cattle health services, and establishing strong institutional support systems can help dairy farmers become more resilient to climate change and protect their livelihoods. Full article

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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13 pages, 1543 KiB

Open AccessSystematic Review

A Systematic Review of Agroecology Strategies for Adapting to Climate Change Impacts on Smallholder Crop Farmers’ Livelihoods in South Africa

by Mashford Zenda and Michael Rudolph

Climate 2024, 12(3), 33; https://doi.org/10.3390/cli12030033 - 27 Feb 2024

Viewed by 1773

Abstract

This systematic review identified the prevalence, effectiveness, and potential benefits of agroecology strategies in promoting sustainable agriculture practices implemented by smallholder crop farmers in South Africa. The review carried out a comprehensive literature search across various academic databases, including PubMed, Scopus, and Web [...] Read more.

This systematic review identified the prevalence, effectiveness, and potential benefits of agroecology strategies in promoting sustainable agriculture practices implemented by smallholder crop farmers in South Africa. The review carried out a comprehensive literature search across various academic databases, including PubMed, Scopus, and Web of science. The relevant studies were screened and selected based on predetermined inclusion criteria where a total of 262 articles were extracted and reduced to 30 articles for this systematic review. Data were extracted and synthesised to classify patterns and trends in the adoption of agroecology elements. The results obtained from the review of this study highlights the identification of specific strategies such as indigenous crop varieties, conservation agriculture, intercropping, agroforestry, drought-tolerant crop varieties, and water management strategies. These outcomes demonstrated insights into the prevalence of different strategies applied by smallholder crop farmers in South Africa. Furthermore, the review determined the reported benefits, such as increased crop resilience, improved soil fertility, and enhanced water use efficiency. These benefits were assessed on the available evidence from the selected studies. This review contributes to a better understanding of agroecology practices in South African. The results can inform policymakers, researchers, and farmers in developing appropriate strategies to enhance sustainable agricultural practices. Full article

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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29 pages, 6941 KiB

Open AccessArticle

Analyzing Rainfall Trends Using Statistical Methods across Vaippar Basin, Tamil Nadu, India: A Comprehensive Study

by Manikandan Muthiah, Saravanan Sivarajan, Nagarajan Madasamy, Anandaraj Natarajan and Raviraj Ayyavoo

Sustainability 2024, 16(5), 1957; https://doi.org/10.3390/su16051957 - 27 Feb 2024

Viewed by 603

Abstract

The Vaippar basin in southern India is economically important for rainfed and irrigated agriculture, mainly depending on the northeast monsoon (NEM) during October–December, and any changes in rainfall patterns directly affect crop ecosystems. This study aimed to analyze spatio-temporal rainfall changes using the [...] Read more.

The Vaippar basin in southern India is economically important for rainfed and irrigated agriculture, mainly depending on the northeast monsoon (NEM) during October–December, and any changes in rainfall patterns directly affect crop ecosystems. This study aimed to analyze spatio-temporal rainfall changes using the monthly data from 13 scattered rain gauge stations in the Vaippar basin, India. They were converted into gridded rainfall data by creating 26 equally spaced grids with a spacing of 0.125° × 0.125° for the period between 1971 and 2019 through interpolation technique. Three methods, namely Simple Linear Regression (SLR), Mann–Kendell/modified Mann–Kendell (MK/MMK), and Sen’s Innovation trend analysis (ITA), were employed to detect trends and magnitudes for annual and seasonal gridded rainfall series. The results showed significant trends at 2.3%, 7.7%, and 44.6% of grid points using SLR, MK/MMK, and ITA methods, respectively. Notably, ITA analysis revealed significant trends in annual and NEM rainfall at 57.69% and 76.92% of the grid points, respectively, at a 5% significance level. The southwestern and central parts of the basin exhibited a higher number of significant upward trends in annual rainfall. Similarly for the NEM season, the south-eastern, central, and extreme southern parts experienced significant upward trend. The western part of the basin exhibited significantly upward trend with a slope value of 2.03 mm/year, while the central part showed non-significant downward trend with a slope value of −1.89 mm/year for the NEM series. This study used the advantage of ITA method, allowing for exploration of monotonic/non-monotonic trends, as well as subtrends of low, medium, and high rainfall segments within the series. The key findings of this study serve as a scientific report from a policy perspective, aiding in the preparation and management of extreme climate effects on land and water resources in the Vaipaar basin. Full article

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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27 pages, 8244 KiB

Open AccessArticle

Intra-Annual Cumulative Effects and Mechanisms of Climatic Factors on Global Vegetation Biomes’ Growth

by Guoming Du, Shouhong Yan, Hang Chen, Jian Yang and Youyue Wen

Remote Sens. 2024, 16(5), 779; https://doi.org/10.3390/rs16050779 - 23 Feb 2024

Viewed by 491

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

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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15 pages, 754 KiB

Open AccessArticle

Environmental Management of Ecuador’s Business Sector in the Fight against Climate Change

by Miguel Aizaga, Marcelo Ramírez, María Carmen Colmenárez Mujica and Renato M. Toasa

Sustainability 2024, 16(5), 1837; https://doi.org/10.3390/su16051837 - 23 Feb 2024

Viewed by 457

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

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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20 pages, 12932 KiB

Open AccessArticle

Enhancing Maize Yield Simulations in Regional China Using Machine Learning and Multi-Data Resources

by Yangfeng Zou, Giri Raj Kattel and Lijuan Miao

Remote Sens. 2024, 16(4), 701; https://doi.org/10.3390/rs16040701 - 16 Feb 2024

Cited by 1 | Viewed by 664

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

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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18 pages, 3401 KiB

Open AccessArticle

Visualising the Relevance of Climate Change for Spatial Planning by the Example of Serbia

by Marijana Pantić, Tamara Maričić and Saša Milijić

Appl. Sci. 2024, 14(4), 1530; https://doi.org/10.3390/app14041530 - 14 Feb 2024

Viewed by 506

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

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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12 pages, 265 KiB

Open AccessArticle

Addressing the Climate Change Adaptation Gap: Key Themes and Future Directions

by Ishfaq Hussain Malik and James D. Ford

Climate 2024, 12(2), 24; https://doi.org/10.3390/cli12020024 - 08 Feb 2024

Viewed by 2965

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

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

18 pages, 4216 KiB

Open AccessArticle

The Variation Characteristics of Stratospheric Circulation under the Interdecadal Variability of Antarctic Total Column Ozone in Early Austral Spring

by Jiayao Li, Shunwu Zhou, Dong Guo, Dingzhu Hu, Yao Yao and Minghui Wu

Remote Sens. 2024, 16(4), 619; https://doi.org/10.3390/rs16040619 - 07 Feb 2024

Viewed by 634

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

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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26 pages, 10782 KiB

Open AccessArticle

Adaptation of Tree Species in the Greater Khingan Range under Climate Change: Ecological Strategy Differences between Larix gmelinii and Quercus mongolica

by Bingyun Du, Zeqiang Wang, Xiangyou Li, Xi Zhang, Xuetong Wang and Dongyou Zhang

Forests 2024, 15(2), 283; https://doi.org/10.3390/f15020283 - 02 Feb 2024

Viewed by 787

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

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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22 pages, 3277 KiB

Open AccessReview

Net Zero Dairy Farming—Advancing Climate Goals with Big Data and Artificial Intelligence

by Suresh Neethirajan

Climate 2024, 12(2), 15; https://doi.org/10.3390/cli12020015 - 25 Jan 2024

Cited by 1 | Viewed by 2765

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

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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22 pages, 2926 KiB

Open AccessReview

Meta-Analysis of Life Cycle Assessment Studies for Polyethylene Terephthalate Water Bottle System

by Yoo-Jin Go, Dong-Ho Kang, Hyun-Jin Park, Jun-Hyuk Lee and Jin-Kie Shim

Sustainability 2024, 16(2), 535; https://doi.org/10.3390/su16020535 - 08 Jan 2024

Cited by 1 | Viewed by 1310

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

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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22 pages, 5698 KiB

Open AccessArticle

Estimation of the Short-Term Impact of Climate-Change-Related Factors on Wood Supply in Poland in 2023–2025

by Jan Kotlarz and Sylwester Bejger

Forests 2024, 15(1), 108; https://doi.org/10.3390/f15010108 - 05 Jan 2024

Viewed by 871

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

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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