Climate Change Impacts and Adaptation: Interdisciplinary Perspectives

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Agronomy agronomy	3.3	6.2	2011	17.6 Days	CHF 2600
Applied Sciences applsci	2.5	5.3	2011	18.4 Days	CHF 2400
Climate climate	3.0	5.5	2013	19.7 Days	CHF 1800
Forests forests	2.4	4.4	2010	16.2 Days	CHF 2600
Remote Sensing remotesensing	4.2	8.3	2009	23.9 Days	CHF 2700
Sustainability sustainability	3.3	6.8	2009	19.7 Days	CHF 2400
ISPRS International Journal of Geo-Information ijgi	2.8	6.9	2012	35.8 Days	CHF 1900

20 pages, 5709 KiB

Open AccessArticle

Agriculture Resilient at Three Irrigation Modules of Zacatecas, Mexico: Water Scarcity and Climate Variability

by Carlos Bautista-Capetillo, Hugo Pineda-Martínez, Luis Alberto Flores-Chaires and Luis Felipe Pineda-Martínez

Agronomy 2025, 15(4), 800; https://doi.org/10.3390/agronomy15040800 - 24 Mar 2025

Viewed by 181

Abstract

Agriculture is the largest consumer of freshwater resources, accounting for approximately 70% of total water withdrawals. In semi-arid regions like Zacatecas, Mexico, water scarcity and climate variability pose critical challenges to small-scale farmers. This study evaluates the effectiveness of integrating modern irrigation technologies [...] Read more.

Agriculture is the largest consumer of freshwater resources, accounting for approximately 70% of total water withdrawals. In semi-arid regions like Zacatecas, Mexico, water scarcity and climate variability pose critical challenges to small-scale farmers. This study evaluates the effectiveness of integrating modern irrigation technologies with traditional water management practices to enhance agricultural resilience. Analysis of climatic data (1961–2020) revealed a statistically significant increase in annual precipitation of 2.01 mm year⁻¹ in the Leobardo Reynoso module (p < 0.05), while the Miguel Alemán module exhibited a decline ranging from −0.54 mm year⁻¹ to −2.22 mm year⁻¹, exacerbating water scarcity. Pressurized irrigation systems in Leobardo Reynoso improved application efficiency to 87.5%, compared to 50% in traditional furrow irrigation. Despite these advancements, conveyance efficiency remains low (60%) due to extensive open canal networks. Climate projections indicate a 6–11% increase in irrigation water demand for staple crops by 2065, driven by rising evapotranspiration rates. Findings underscore the need for policy interventions, infrastructure upgrades, and financial support to sustain agricultural productivity in water-stressed environments. Full article

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

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22 pages, 691 KiB

Open AccessArticle

Linking Perceptions, Emotions, and Actions: How Psychological Distance, Media Framing, and Guilt About Climate Crisis Promote Communication and Pro-Environmental Behavior

by Juhyun Hong and Chang-Young Jeon

Sustainability 2025, 17(6), 2409; https://doi.org/10.3390/su17062409 - 10 Mar 2025

Viewed by 270

Abstract

This study explored the impact of psychological distance, media coverage, and guilt on communication behavior and eco-friendly actions and found that environmental interest was a significant predictor of behavior. The findings indicate that perceptions of the severity of the climate crisis and media [...] Read more.

This study explored the impact of psychological distance, media coverage, and guilt on communication behavior and eco-friendly actions and found that environmental interest was a significant predictor of behavior. The findings indicate that perceptions of the severity of the climate crisis and media coverage facilitated information seeking and interpersonal communication, which in turn led to eco-friendly behavior. Additionally, guilt strongly predicted information seeking and eco-friendly product purchase intention. Information seeking and interpersonal communication positively influenced eco-friendly product purchases and energy conservation. Women and younger individuals favored face-to-face communication and public transport, while older individuals focused on energy conservation and eco-friendly purchases. Perceptions of climate crisis severity and media coverage influenced communication and eco-friendly purchases. Guilt strongly predicted information seeking and purchase intention, which emphasizes the effectiveness of emotion-based messages. The findings highlight the need for targeted strategies across demographics and political orientations to promote pro-environmental behavior. Full article

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

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20 pages, 4447 KiB

Open AccessArticle

Risk Spillover Effects in Energy Markets Under Climate Change: Evidence from the Chinese Market

by Shufen Cao, Min Pang, Yongtan Ma, Qianyu Dong and Yongping Tao

Sustainability 2025, 17(5), 2126; https://doi.org/10.3390/su17052126 - 1 Mar 2025

Viewed by 470

Abstract

To ascertain the impact of climate change on risk spillovers in energy markets, the vector autoregressive (VAR) model and the impulse response function (IRF) were utilized to analyze risk spillover effects in China’s energy markets between 2007 and 2023. The findings indicated that [...] Read more.

To ascertain the impact of climate change on risk spillovers in energy markets, the vector autoregressive (VAR) model and the impulse response function (IRF) were utilized to analyze risk spillover effects in China’s energy markets between 2007 and 2023. The findings indicated that the risk spillover from climate change in China’s energy markets is characterized by asymmetric and time-varying characteristics. A substantial degree of heterogeneity exists among distinct energy markets. Climate physical risk has a detrimental effect on risk spillovers in energy markets, while transition risk has a positive impact on risk spillover in fuel, LPG, and natural gas markets, and a negative effect on risk spillover in alcohol, gasoline, and diesel markets. Full article

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

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40 pages, 9921 KiB

Open AccessArticle

Geoinformatics and Machine Learning for Shoreline Change Monitoring: A 35-Year Analysis of Coastal Erosion in the Upper Gulf of Thailand

by Chakrit Chawalit, Wuttichai Boonpook, Asamaporn Sitthi, Kritanai Torsri, Daroonwan Kamthonkiat, Yumin Tan, Apised Suwansaard and Attawut Nardkulpat

ISPRS Int. J. Geo-Inf. 2025, 14(2), 94; https://doi.org/10.3390/ijgi14020094 - 19 Feb 2025

Viewed by 1037

Abstract

Coastal erosion is a critical environmental challenge in the Upper Gulf of Thailand, driven by both natural processes and human activities. This study analyzes 35 years (1988–2023) of shoreline changes using geoinformatics, machine learning algorithms (Random Forest, Support Vector Machine, Maximum Likelihood, Minimum [...] Read more.

Coastal erosion is a critical environmental challenge in the Upper Gulf of Thailand, driven by both natural processes and human activities. This study analyzes 35 years (1988–2023) of shoreline changes using geoinformatics, machine learning algorithms (Random Forest, Support Vector Machine, Maximum Likelihood, Minimum Distance), and the Digital Shoreline Analysis System (DSAS). The results show that the Random Forest algorithm, utilizing spectral bands and indices (NDVI, NDWI, MNDWI, SAVI), achieved the highest classification accuracy (98.17%) and a Kappa coefficient of 0.9432, enabling reliable delineation of land and water boundaries. The extracted annual shorelines were validated with high accuracy, yielding RMSE values of 13.59 m (2018) and 8.90 m (2023). The DSAS analysis identified significant spatial and temporal variations in shoreline erosion and accretion. Between 1988 and 2006, the most intense erosion occurred in regions 4 and 5, influenced by sea-level rise, strong monsoonal currents, and human activities. However, from 2006 to 2018, erosion rates declined significantly, attributed to coastal protection structures and mangrove restoration. The period 2018–2023 exhibited a combination of erosion and accretion, reflecting dynamic sediment transport processes and the impact of coastal management measures. Over time, erosion rates declined due to the implementation of protective structures (e.g., bamboo fences, rock revetments) and the natural expansion of mangrove forests. However, localized erosion remains persistent in low-lying, vulnerable areas, exacerbated by tidal forces, rising sea levels, and seasonal monsoons. Anthropogenic activities, including urban development, mangrove deforestation, and aquaculture expansion, continue to destabilize shorelines. The findings underscore the importance of sustainable coastal management strategies, such as mangrove restoration, soft engineering coastal protection, and integrated land-use planning. This study demonstrates the effectiveness of combining machine learning and geoinformatics for shoreline monitoring and provides valuable insights for coastal erosion mitigation and enhancing coastal resilience in the Upper Gulf of Thailand. Full article

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

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13 pages, 2806 KiB

Open AccessArticle

GIS-Based Dashboards as Advanced Geospatial Applications for Climate Change Education and Teaching the Future

by Rafael De Miguel González, Juan Mar-Beguería, María Sebastián López and Ondrej Kratochvíl

ISPRS Int. J. Geo-Inf. 2025, 14(2), 89; https://doi.org/10.3390/ijgi14020089 - 18 Feb 2025

Viewed by 1089

Abstract

ArcGIS Dashboard technology allows for the integration and visualization of various maps, charts, and indicators within a single interface, using databases underneath a geographic information system. The two dashboards of the European project Teaching the Future address the dual objective of (i) cartographically [...] Read more.

ArcGIS Dashboard technology allows for the integration and visualization of various maps, charts, and indicators within a single interface, using databases underneath a geographic information system. The two dashboards of the European project Teaching the Future address the dual objective of (i) cartographically displaying the evolution in four phases of climate change data experienced across the entire planet from 1954 to 2021 in vectorial cells measuring one degree of latitude by one degree of longitude and (ii) spatially representing three scenarios (low, medium, and high greenhouse gas emissions) up to the year 2100, showing potential temperature increases in those same cells. In addition to the maps, the different data and charts contribute to the understanding of anomalies relative to the average, the global increase in each selected area by zooming in on the map, and the evolution of both observed and projected data. Both dashboards represent an accurate and reliable treatment of the data, as well as a cartographic expression that is easy for map readers to understand, making them powerful resources for teaching climate change at any educational level, whether in higher education or schools and for a general audience. Full article

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

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21 pages, 1868 KiB

Open AccessReview

Climate Change and Arbovirus: A Review and Bibliometric Analysis

by Maryly Weyll Sant’Anna, Maurício Lamano Ferreira, Leonardo Ferreira da Silva and Pedro Luiz Côrtes

Climate 2025, 13(2), 35; https://doi.org/10.3390/cli13020035 - 6 Feb 2025

Viewed by 792

Abstract

The rise in Earth’s temperature is capable of influencing the occurrence of catastrophic natural events, contributing to outbreaks of arboviruses in endemic areas and new geographical regions. This study aimed to conduct a bibliometric review and analysis of research activities on climate change [...] Read more.

The rise in Earth’s temperature is capable of influencing the occurrence of catastrophic natural events, contributing to outbreaks of arboviruses in endemic areas and new geographical regions. This study aimed to conduct a bibliometric review and analysis of research activities on climate change with a focus on human arboviruses, using the Scopus database. A total of 1644 documents were found related to the topic between 1934 and 2023. The United States continues to lead in the number of academic publications. Dengue was the arbovirosis with the highest number of publications, followed by West Nile fever, Zika and chikungunya fever. Due to the rise in global temperature, a trend of arbovirus dissemination to non-endemic areas is observed, with a possible global increase in morbidity and mortality. Consequently, more effective measures are expected from epidemiological surveillance, vector control services, governmental authorities and, crucially, social engagement in combating and preventing new outbreaks. Full article

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

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16 pages, 10845 KiB

Open AccessArticle

Recent Spatiotemporal Changes of Subhourly Extreme Rainfall Events in Seoul

by Ju-Young Shin, Jiyeon Park, Kyungmin Sung and Yongseok Kim

Appl. Sci. 2025, 15(3), 1672; https://doi.org/10.3390/app15031672 - 6 Feb 2025

Viewed by 657

Abstract

This study aims to examine the spatiotemporal variations of extreme rainfall events in Seoul, South Korea, utilizing subhourly rainfall data collected from an extensive observation network. Employing the Mann–Kendall trend detection test and Moran’s I index, this study analyzed temporal trends and spatial [...] Read more.

This study aims to examine the spatiotemporal variations of extreme rainfall events in Seoul, South Korea, utilizing subhourly rainfall data collected from an extensive observation network. Employing the Mann–Kendall trend detection test and Moran’s I index, this study analyzed temporal trends and spatial distributions in the extreme rainfall time series at 37 weather stations. The findings revealed that the annual maximum precipitation (AMP) series for various durations in Seoul generally exhibited a decreasing trend, with a marked decline observed for durations of 300 and 360 min. Furthermore, the study identified notable changes in the spatial patterns of AMP events, particularly for subhourly AMP events. The results indicate an intensification in the spatial concentration of AMP distribution. Consequently, despite the overall reduction in AMP, the likelihood of urban flooding may increase. This suggests that existing hydraulic design criteria, based on past concepts that temporal and spatial variability are constant, may no longer adequately represent extreme rainfall events. Therefore, revising these criteria to account for the evolving nature of extreme rainfall patterns is imperative. Full article

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

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18 pages, 8681 KiB

Open AccessArticle

Potential Impacts of Climate Change on the Spatial Distribution Pattern of Naked Oats in China

by Zhenwei Yang, Xujing Yang, Yuheng Huang, Yalin Zhang, Yao Guo, Meichen Feng, Mingxing Qin, Ning Jin, Muhammad Amjad, Chao Wang, Meijun Zhang and Wude Yang

Agronomy 2025, 15(2), 362; https://doi.org/10.3390/agronomy15020362 - 30 Jan 2025

Viewed by 735

Abstract

Naked oats, a significant minor cereal crop in China popular for its nutrient richness, have experienced a surge in production in recent years, fueled by the escalating demand for wholesome healthy food. However, the dispersed and disorganized cultivation plan of naked oats poses [...] Read more.

Naked oats, a significant minor cereal crop in China popular for its nutrient richness, have experienced a surge in production in recent years, fueled by the escalating demand for wholesome healthy food. However, the dispersed and disorganized cultivation plan of naked oats poses a significant constraint on its industrial progression. Considering the dual influence of cultivation, management techniques, and global climate change on the production of naked oats, this study explores the potential impacts of climate change on the spatial distribution and yield of this cereal crop. Leveraging CMIP6 climate models (BCC-CSM2-MR, CanESM5, CNRM-ESM2-1) and an optimized MaxEnt model (RM = 0.5, FC = LQ), we simulated potential climate-suitable zones for naked oats from 1990 to 2020 and forecasted alterations under various emission scenarios from 2021 to 2100. The model achieved an average accuracy test with high value (AUC = 0.945) in predicting suitable areas; with precipitation seasonality (Coefficient of Variation) (bio15, 21.70%) and topsoil pH (H₂O) (T_PH_H₂O, 21.00%) as key factors, both climate and soil properties have a greater influence. Simulation results showed that the climatically suitable area for naked oats increased under all scenarios, with the largest increase in the optimal growing area under ssp126 in the 2030s. The increase was 3.93% with an area of 0.77 × 10⁶ km². The study also compared the data from the main producing counties of naked oats in Shanxi Province from 2020 to 2022 for statistical purposes, and found that 39 counties were in high climatic suitability zones and 39 counties were in remarkably high climatic suitability zones. The agreement rate between planting areas and climatically suitable areas was as high as 97.44%. Further, the growing area expanded westward, increasing the production intensity. This study reveals the current spatial distribution pattern of naked oats, providing a scientific rationale for addressing climate change through multi-scenario predictions. Our findings have implications for optimizing cultivation layout and identifying optimal zones, supporting sustainable agricultural development strategies in China. Full article

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

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18 pages, 4959 KiB

Open AccessFeature PaperArticle

Timing of Drought and Severity of Induced Leaf Desiccation Affect Recovery, Growth and Autumnal Leaf Senescence in Fagus sylvatica L. Saplings

by Kristine Vander Mijnsbrugge, Mattias Bollen, Stefaan Moreels, Eduardo Notivol Paino, Kris Vandekerkhove, Luc De Keersmaeker, Arno Thomaes, Sanne Verdonck and Margot Vanhellemont

Forests 2025, 16(1), 5; https://doi.org/10.3390/f16010005 - 24 Dec 2024

Viewed by 593

Abstract

Increased water limitations due to climate change will pose severe challenges to forest ecosystems in Europe. We investigated the response of potted saplings of Fagus sylvatica L., one of the major European tree species, to a spring and a summer water-withholding period with [...] Read more.

Increased water limitations due to climate change will pose severe challenges to forest ecosystems in Europe. We investigated the response of potted saplings of Fagus sylvatica L., one of the major European tree species, to a spring and a summer water-withholding period with control–control (C-C), control–drought (C-D), drought–control (D-C) and drought–drought (D-D) treatments. We focused on recovery capacity and phenological and growth traits and questioned the extent to which an earlier drought influenced the response to a second drought in the same growing season. To examine the impact of the level of drought stress, a distinction was made between saplings with less or more than half of their leaves desiccated due to the spring drought (D<50 and D>50). The timing of the drought influenced the immediate post-drought response: saplings severely affected by the spring drought (D>50) resprouted, whereas saplings severely affected by the summer drought (C-D and D<50-D) did not. The spring treatment influenced the onset of visual symptoms in the summer drought, with saplings less affected in the spring drought (D<50-D) developing symptoms three days later than the saplings not subjected to drought in the spring (C-D), whereas severely affected saplings (D>50-D) had not yet display symptoms seventeen days after the first visual symptoms in the spring control saplings (C-D). The timing of autumnal leaf senescence displayed the legacies of the spring treatment. The saplings heavily affected by the spring drought showed a slower decrease in relative chlorophyll content and delayed leaf senescence (D>50-C and D>50-D), which may enable the repair of damaged tissues. The saplings that were less affected by the spring drought (D<50-C) showed earlier autumnal leaf senescence, which is likely an acclimation response. Interestingly, a larger diameter increment in autumn for all of the saplings that experienced the summer drought (C-D, D<50-D and D>50-D) may indicate the recovery of hydraulic capacity by new xylem growth. Our results underline the plasticity of young F. sylvatica saplings in response to (repeated) drought. Full article

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

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33 pages, 9196 KiB

Open AccessArticle

Integrating Remote Sensing and Community Perceptions for Sustainable Climate Adaptation Strategies in Mountain Ecosystems

by Ankita Pokhrel, Ping Fang and Gaurav Bastola

Sustainability 2025, 17(1), 18; https://doi.org/10.3390/su17010018 - 24 Dec 2024

Cited by 1 | Viewed by 761

Abstract

Mountain ecosystems, such as Nepal’s Annapurna Conservation Area (ACA), are highly vulnerable to climate change, which threatens biodiversity, water resources, and livelihoods. This study examines Land Use Land Cover (LULC) changes, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Snow Index (NDSI), climate [...] Read more.

Mountain ecosystems, such as Nepal’s Annapurna Conservation Area (ACA), are highly vulnerable to climate change, which threatens biodiversity, water resources, and livelihoods. This study examines Land Use Land Cover (LULC) changes, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Snow Index (NDSI), climate variability, and community perception and adaptations over a 35-year period (1988–2023) using remote sensing, meteorological data, and community surveys. Vegetation expanded by 19,800 hectares, while barren land declined, reflecting afforestation and land reclamation efforts. NDVI showed improved vegetation health, while NDSI revealed significant snow cover losses, particularly after 1996. Meteorological analysis highlighted intensifying monsoonal rainfall and rising extreme precipitation events at lower elevations. Communities reported increased flooding, unpredictable rainfall, and reduced snowfall, driving adaptive responses such as water conservation, crop diversification, and rainwater harvesting. These findings demonstrate the value of integrating scientific data with local knowledge to inform sustainable adaptation strategies. Contributing to Sustainable Development Goals (SDGs) 6 and 13, the findings emphasize the importance of adaptive water management, resilient agriculture, and participatory conservation to enhance climate resilience in mountain ecosystems. Full article

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

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31 pages, 1428 KiB

Open AccessReview

Changes in Climate and Their Implications for Cattle Nutrition and Management

by Bashiri Iddy Muzzo, R. Douglas Ramsey and Juan J. Villalba

Climate 2025, 13(1), 1; https://doi.org/10.3390/cli13010001 - 24 Dec 2024

Cited by 1 | Viewed by 1804

Abstract

Climate change is a global challenge that impacts rangeland and pastureland landscapes by inducing shifts in temperature variability, precipitation patterns, and extreme weather events. These changes alter soil and plant conditions, reducing forage availability and chemical composition and leading to nutritional stress in [...] Read more.

Climate change is a global challenge that impacts rangeland and pastureland landscapes by inducing shifts in temperature variability, precipitation patterns, and extreme weather events. These changes alter soil and plant conditions, reducing forage availability and chemical composition and leading to nutritional stress in cattle. This stress occurs when animals lack adequate water and feed sources or when these resources are insufficient in quantity, composition, or nutrient balance. Several strategies are essential to address these impacts. Genetic selection, epigenetic biomarkers, and exploration of epigenetic memories present promising avenues for enhancing the resilience of cattle populations and improving adaptation to environmental stresses. Remote sensing and GIS technologies assist in locating wet spots to establish islands of plant diversity and high forage quality for grazing amid ongoing climate change challenges. Establishing islands of functional plant diversity improves forage quality, reduces carbon and nitrogen footprints, and provides essential nutrients and bioactives, thus enhancing cattle health, welfare, and productivity. Real-time GPS collars coupled with accelerometers provide detailed data on cattle movement and activity, aiding livestock nutrition management while mitigating heat stress. Integrating these strategies may offer significant advantages to animals facing a changing world while securing the future of livestock production and the global food system. Full article

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

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26 pages, 17376 KiB

Open AccessArticle

Analysis of Future Drought Risk and Wheat Meteorological Disaster in Ningxia (Northwest China) Based on CMIP6 and SPEI

by Xinlong Li, Junli Tan, Xina Wang, Qian Shang, Hao Li and Xuefang Li

Agronomy 2024, 14(12), 3051; https://doi.org/10.3390/agronomy14123051 - 20 Dec 2024

Viewed by 666

Abstract

In arid areas, droughts caused by climate change seriously impact wheat production. Therefore, research on spatial and temporal variability of dry and hot wind events and drought risk under different development patterns of future climate can provide a reference for wheat cultivation planning [...] Read more.

In arid areas, droughts caused by climate change seriously impact wheat production. Therefore, research on spatial and temporal variability of dry and hot wind events and drought risk under different development patterns of future climate can provide a reference for wheat cultivation planning in the study area. Based on meteorological data under three scenarios of the CMIP6 (Sixth International Coupled Model Comparison Program) shared socio-economic path (SSP), we introduced wheat dry hot wind discrimination criteria and calculated the Standardized Precipitation–Evapotranspiration Index (SPEI). Future temperature changes within the Ningxia Province were consistent, increasing at a rate of 0.037, 0.15 and 0.45 °C·(10 a⁻¹) under SSP126, 245 and 585 scenarios, respectively. Simultaneously, average annual precipitation would increase by 17.77, 38.73 and 32.12 mm, respectively. Dry hot wind frequency differed spatially, being higher in northern Ningxia and western Ningxia, and lower in southern Ningxia and eastern Ningxia. During the wheat growing period, there is an obvious increasing drought risk trend under the SSP585 model in May, and the possibility of drought risk in the middle period was highest under the SSP126 model. In June, SPEI was generally higher than in May, and the risk of alternating drought and flood was greater under the SSP585 model, while near-medium drought risk was lower under the SSP126 and SSP245 models. The influence of DHW (dry and hot wind) on wheat yield will increase with the increase of warming level. However, when DHW occurs, effective irrigation can mitigate the harm. Irrigation water can be sourced from various channels, including rainfall, diversion, and groundwater. These results provide scientific reference for sustainable agricultural production, drought risk and wheat meteorological disaster forecast in inland arid areas affected by climate change. Full article

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

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10 pages, 1575 KiB

Open AccessArticle

Investigation of Climatic Factors Affecting the Amount of Foraged Matsutake Mushrooms in Korea

by Doo-Ho Choi, Cheol-Soon Ko, Youn-Lee Oh, Ji-Hoon Im, Minji Oh and Eun-Ji Lee

Forests 2024, 15(12), 2165; https://doi.org/10.3390/f15122165 - 9 Dec 2024

Viewed by 855

Abstract

Tricholoma matsutake is a valuable edible mushroom in Eastern Asia. Due to the challenges of artificial cultivation, T. matsutake cultivation has relied on foraging from pine forests. Changes in global climate variables, such as temperature and precipitation, could affect the amount of foraged [...] Read more.

Tricholoma matsutake is a valuable edible mushroom in Eastern Asia. Due to the challenges of artificial cultivation, T. matsutake cultivation has relied on foraging from pine forests. Changes in global climate variables, such as temperature and precipitation, could affect the amount of foraged T. matsutake. In this study, we investigated the correlation between the amount of foraged T. matsutake and climatic factors (average monthly temperature and precipitation) in Yangyang-gun using the augmented Dickey–Fuller test and the ordinary least squares method. Among the assessed correlations between the foraged T. matsutake and different climatic factors, the average temperature in August was significantly correlated with the amount of foraged T. matsutake, increasing by 1.5 tons when the temperature in August increased by 1 unit. Overall, this study identified a potentially strong positive correlation between the average temperature in August and amount of foraged T. matsutake. Full article

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

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23 pages, 14457 KiB

Open AccessArticle

Riders Under the Heat: Exploring the Impact of Extreme Heat on the Integration of Bike-Sharing and Public Transportation in Shenzhen, China

by Xin Wang, Rui Xue, Ming Lu and Jiangyue Wu

ISPRS Int. J. Geo-Inf. 2024, 13(12), 438; https://doi.org/10.3390/ijgi13120438 - 5 Dec 2024

Cited by 1 | Viewed by 1075

Abstract

Bike-sharing (BS) systems provide a widely used and convenient feeder mode for connecting to public transportation (PT) and is seen as an effective solution to the first- and last-mile problem. Amidst the critical challenges posed by global climate change and rising temperatures, enhancing [...] Read more.

Bike-sharing (BS) systems provide a widely used and convenient feeder mode for connecting to public transportation (PT) and is seen as an effective solution to the first- and last-mile problem. Amidst the critical challenges posed by global climate change and rising temperatures, enhancing the resilience of the BS and PT integration is essential to ensure sustainable urban mobility and adapt to increasing climate variability, yet empirical studies in this area remain limited. This study analyzes BS-PT integration usage under extreme heats events, focusing on a Chinese mega city’s bike-sharing system. By defining extreme heat using the heat index, a more accurate measure of heat perception is established. We carefully categorize heatwaves based on the duration and temperature context of extreme heat to account for their potential impact on the integration’s response. Then, integrating multi-source big data and applying geographically weighted regression (GWR), we explore the spatial–temporal variations in the response of BS-PT integration ridership during different temperatures, and further identify key factors that contribute to the response of BS-PT integrated travel. Results show that extreme heat significantly influences BS-PT integration, with users showing a greater willingness to shift towards more integrated uses under extreme heat during non-summer seasons, compared to solely using bike-sharing, to avoid outdoor heat exposure. The temporal heterogeneity of the integrated trips is highest during extreme heat in non-summer and lowest under continuous extreme-heat periods. GWR spatial regression reveals that land-use characteristics significantly affect BS-PT integration resilience, with notable spatial differences in the influence of various factors, such as office density and entropy. These findings enhance our understanding of how climate change affects public transportation, providing urban planners and policymakers with valuable insights for improving the adaptability of urban mobility systems to climate change. Full article

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

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15 pages, 3793 KiB

Open AccessArticle

A Bibliometric Analysis of Global Research on Climate Change and Agriculture from 1985 to 2023

by Cheng Li, Hongda Yao, Zhaozhe Li, Fang Wu, Bo Liu, Yongping Wu, Kwok Pan Chun, Thanti Octavianti, Xuefeng Cui and Yang Xu

Agronomy 2024, 14(11), 2729; https://doi.org/10.3390/agronomy14112729 - 19 Nov 2024

Viewed by 1354

Abstract

With increasing concentrations of atmospheric greenhouse gases, the interaction between climate change and agriculture is receiving widespread attention as part of food security and sustainable human development. However, a comprehensive summary of knowledge in the field of climate change and agriculture from a [...] Read more.

With increasing concentrations of atmospheric greenhouse gases, the interaction between climate change and agriculture is receiving widespread attention as part of food security and sustainable human development. However, a comprehensive summary of knowledge in the field of climate change and agriculture from a scientometric perspective is still lacking. Here, we selected 25,872 papers related to climate change and agriculture from the Web of Science Core Collection database for the period 1985 to 2023 and used VOSviewer software to reveal the research status and trends. The main results were as follows: (1) the number of papers in this field showed a rapidly increasing trend after 2007, with a clear interdisciplinary characteristic; (2) The United States was the most influential country in this field with 6819 papers and 363,109 citations. China had the second highest number of papers (3722 papers), but the Chinese Academy of Sciences was the most influential institution with the most papers. On an author level, Pete Smith was the most influential; (3) All keywords were divided into four different research topics, such as the impact of climate change on agriculture, climate change mitigation and adaptation in agriculture, and crop growth in response to climate change. Among them, some keywords related to climate change adaptation were the most recent topics of interest in this field. These findings provide effective scientific references for relevant scientists and practitioners to better conduct future theoretical and practical research on climate change and agriculture. Full article

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

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21 pages, 21195 KiB

Open AccessArticle

Mapping the Future: Climate-Induced Changes in Aboveground Live-Biomass Carbon Density Across Mexico’s Coniferous Forests

by Carmela Sandoval-García, Jorge Méndez-González, Flores Andrés, Eulalia Edith Villavicencio-Gutiérrez, Fernando Paz-Pellat, Celestino Flores-López, Eladio Heriberto Cornejo-Oviedo, Alejandro Zermeño-González, Librado Sosa-Díaz, Marino García-Guzmán and José Ángel Villarreal-Quintanilla

Forests 2024, 15(11), 2032; https://doi.org/10.3390/f15112032 - 18 Nov 2024

Viewed by 2306

Abstract

Climate variations in temperature and precipitation significantly impact forest productivity. Precipitation influences the physiology and growth of species, while temperature regulates photosynthesis, respiration, and transpiration. This study developed bioclimatic models to assess how climate change will affect the carbon density of aboveground biomass [...] Read more.

Climate variations in temperature and precipitation significantly impact forest productivity. Precipitation influences the physiology and growth of species, while temperature regulates photosynthesis, respiration, and transpiration. This study developed bioclimatic models to assess how climate change will affect the carbon density of aboveground biomass (_cdAGB) in Mexico’s coniferous forests for 2050 and 2070. We used _cdAGB data from the National Forest and Soils Inventory (INFyS) of Mexico and 19 bioclimatic variables from WorldClim ver. 2.0. The best predictors of _cdAGB were obtained using machine learning techniques with the “caret” library in R. The model was trained with 80% of the data and validated with the remaining 20% using Generalized Linear Models (GLMs). Current _cdAGB prediction maps were generated using the best predictors. Future _cdAGB was calculated with the average of three general circulation models (GCMs) of future climate projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5), under four Representative Concentration Pathways (RCPs): 2.6, 4.5, 6.0, and 8.5 W/m². The results indicate _cdAGB losses in all climate scenarios, reaching up to 15 Mg C ha⁻¹, and could occur under the RCP 8.5 scenario by 2070 in the central region of the country. Temperature-related variables are more important than precipitation variables. Bioclimatic variables can explain up to 20% of the total variance in _cdAGB. The temperature in the study area is expected to increase by 2.66 °C by 2050 and 3.36 °C by 2070, while precipitation is expected to fluctuate by ±10% relative to the current values, which could geographically redistribute the _cdAGB of the country’s coniferous forests. These findings underscore the need for forest management to focus not only on biodiversity conservation but also on the carbon storage capacity of these ecosystems. Full article

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

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19 pages, 8003 KiB

Open AccessArticle

The Impact of Seasonal Climate on Dryland Vegetation NPP: The Mediating Role of Phenology

by Xian Liu, Hengkai Li, Yanbing Zhou, Yang Yu and Xiuli Wang

Sustainability 2024, 16(22), 9835; https://doi.org/10.3390/su16229835 - 11 Nov 2024

Cited by 1 | Viewed by 1221

Abstract

Dryland ecosystems are highly sensitive to climate change, making vegetation monitoring crucial for understanding ecological dynamics in these regions. In recent years, climate change, combined with large-scale ecological restoration efforts, has led significant greening in China’s arid areas. However, the mechanisms through which [...] Read more.

Dryland ecosystems are highly sensitive to climate change, making vegetation monitoring crucial for understanding ecological dynamics in these regions. In recent years, climate change, combined with large-scale ecological restoration efforts, has led significant greening in China’s arid areas. However, the mechanisms through which seasonal climate variations regulate vegetation growth are not yet fully understood. This study hypothesizes that seasonal climate change affects net primary productivity (NPP) of vegetation by influencing phenology. We focused on China’s Windbreak and Sand-Fixation Ecological Function Conservation Areas (WSEFCAs) as representative regions of dryland vegetation. The Carnegie–Ames–Stanford Approach (CASA) model was used to estimate vegetation NPP from 2000 to 2020. To extract phenological information, NDVI data were processed using Savitzky–Golay (S–G) filtering and threshold methods to determine the start of season (SOS) and end of season (EOS). The structural equation model (SEM) was constructed to quantitatively assess the contributions of climate change (temperature and precipitation) and phenology to variations in vegetation NPP, identifying the pathways of influence. The results indicate that the average annual NPP in WSEFCAs increased from 55.55 gC/(m²·a) to 75.01 gC/(m²·a), exhibiting uneven spatial distribution. The pathways through which seasonal climate affects vegetation NPP are more complex and uneven. Summer precipitation directly promoted NPP growth (direct effect = 0.243, p < 0.001) while also indirectly enhancing NPP by significantly advancing SOS (0.433, p < 0.001) and delaying EOS (−0.271, p < 0.001), with an indirect effect of 0.133. This finding highlights the critical role of phenology in vegetation growth, particularly in regions with substantial seasonal climate fluctuations. Although the overall ecological environment of WSEFCAs has improved, significant regional disparities remain, especially in northwestern China. This study introduces causal mediation analysis to systematically explore the mechanisms through which seasonal climate change impacts vegetation NPP in WSEFCAs, providing new insights into the broader implications of climate change and offering scientific support for ecological restoration and management strategies in arid regions. Full article

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

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25 pages, 3719 KiB

Open AccessArticle

Impact of Climate Change on Biodiversity and Implications for Nature-Based Solutions

by Cor A. Schipper, Titus W. Hielkema and Alexander Ziemba

Climate 2024, 12(11), 179; https://doi.org/10.3390/cli12110179 - 7 Nov 2024

Cited by 1 | Viewed by 4757

Abstract

The Intergovernmental Panel on Climate Change (IPCC) provides regular scientific assessments on climate change, its implications, and potential future risks based on estimated energy matrixes and policy pathways. The aim of this publication is to assess the risks climate change poses to biodiversity [...] Read more.

The Intergovernmental Panel on Climate Change (IPCC) provides regular scientific assessments on climate change, its implications, and potential future risks based on estimated energy matrixes and policy pathways. The aim of this publication is to assess the risks climate change poses to biodiversity using projected IPCC climate scenarios for the period 2081–2100, combined with key species-sensitivity indicators and variables as a response to climate change projections. In doing so, we address how climate-change-driven pressures may affect biodiversity. Additionally, a novel causal relationship between extreme ambient temperature exposure levels and the corresponding effects on individual species, noted in this paper as the Upper Thermal-Tolerance Limit and Species Sensitivity Distribution (UTTL-SSD), provides a compelling explanation of how global warming affects biodiversity. Our study indicates that North American and Oceanian sites with humid continental and subtropical climates, respectively, are poised to realize temperature shifts that have been identified as potential key tipping-point triggers. Heat stress may significantly affect approximately 60–90% of mammals, 50% of birds, and 50% of amphibians in North American and Oceanian sites for durations ranging from 5 to 84 days per year from 2080. In the humid temperate oceanic climate of European sites, the climate conditions remain relatively stable; however, moderate cumulative effects on biodiversity have been identified, and additional biodiversity-assemblage threat profiles exist to represent these. Both the integration of IPCC-IUCN profiles and the UTTL-SSD response relationship for the species communities considered have resulted in the identification of the projected threats that climate pressures may impose under the considered IPCC scenarios, which would result in biodiversity degradation. The UTTL-SSD responses developed can be used to highlight potential breakdowns among trophic levels in food web structures, highlighting an additional critical element when addressing biodiversity and ecosystem concerns. Full article

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

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27 pages, 30189 KiB

Open AccessArticle

A Novel Approach for Ex Situ Water Quality Monitoring Using the Google Earth Engine and Spectral Indices in Chilika Lake, Odisha, India

by Subhasmita Das, Debabrata Nandi, Rakesh Ranjan Thakur, Dillip Kumar Bera, Duryadhan Behera, Bojan Đurin and Vlado Cetl

ISPRS Int. J. Geo-Inf. 2024, 13(11), 381; https://doi.org/10.3390/ijgi13110381 - 30 Oct 2024

Cited by 2 | Viewed by 2445

Abstract

Chilika Lake, a RAMSAR site, is an environmentally and ecologically pivotal coastal lagoon in India facing significant emerging environmental challenges due to anthropogenic activities and natural processes. Traditional in situ water quality monitoring methods are often labor intensive and time consuming. This study [...] Read more.

Chilika Lake, a RAMSAR site, is an environmentally and ecologically pivotal coastal lagoon in India facing significant emerging environmental challenges due to anthropogenic activities and natural processes. Traditional in situ water quality monitoring methods are often labor intensive and time consuming. This study presents a novel approach for ex situ water quality monitoring in Chilika Lake, located on the east coast of India, utilizing Google Earth Engine (GEE) and spectral indices, such as the Normalized Difference Turbidity Index (NDTI), Normalized Difference Chlorophyll Index (NDCI), and total suspended solids (TSS). The methodology involves the integration of multi-temporal satellite imagery and advanced spectral indices to assess key water quality parameters, such as turbidity, chlorophyll-a concentration, and suspended sediments. The NDTI value in Chilika Lake increased from 2019 to 2021, and the Automatic Water Extraction Index (AWEI) method estimated the TSS concentration. The results demonstrate the effectiveness of this approach in providing accurate and comprehensive water quality assessments, which are crucial for the sustainable management of Chilika Lake. Maps and visualization are presented using GIS software. This study can effectively detect floating algal blooms, identify pollution sources, and determine environmental changes over time. Developing intuitive dashboards and visualization tools can help stakeholders engage with data-driven insights, increase community participation in conservation, and identify pollution sources. Full article

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

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16 pages, 8387 KiB

Open AccessArticle

Examining the Causal and Heterogeneous Influence of Three-Dimensional Urban Forms on CO₂ Emissions in 285 Chinese Cities

by Weiting Xiong, Yedong Zhang and Jingang Li

ISPRS Int. J. Geo-Inf. 2024, 13(11), 372; https://doi.org/10.3390/ijgi13110372 - 22 Oct 2024

Viewed by 1027

Abstract

Despite the efforts to examine the influence of urban forms on CO₂ emissions, most studies have mainly measured urban forms from a two-dimensional perspective, with relatively little attention given to three-dimensional urban forms and their causal relationships. Utilizing the built-up area dataset [...] Read more.

Despite the efforts to examine the influence of urban forms on CO₂ emissions, most studies have mainly measured urban forms from a two-dimensional perspective, with relatively little attention given to three-dimensional urban forms and their causal relationships. Utilizing the built-up area dataset from the Global Human Settlement Layer (GHSL) project and the carbon emission dataset from the China City Greenhouse Gas Working Group (CCG), we examine a causal and heterogeneous effect of three-dimensional urban forms on CO₂ emissions—specifically urban height, density, and intensity—in 285 Chinese cities. The empirical results reveal a robust and positive causal effect of 3D urban forms on carbon emissions. Even when incorporating the spatial spillover effect, the positive effect of 3D urban forms remains. Moreover, GDP per capita and total population have a greater impact on urban CO₂ emissions. Additionally, we find that the influence of 3D urban forms on CO₂ emissions is U-shaped, with total population serving as a moderating factor in this effect. Importantly, there is significant geographic and sectoral heterogeneity in the influence of 3D urban forms on CO₂ emissions. Specifically, the influence of 3D urban forms is greater in eastern cities than in non-eastern cities. Furthermore, 3D urban forms primarily influence household carbon emissions rather than industrial and transportation carbon emissions. Therefore, in response to the growing challenges of global climate change and environmental issues, urban governments should adopt various strategies to develop more rational three-dimensional urban forms to reduce CO₂ emissions. Full article

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

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18 pages, 34062 KiB

Open AccessArticle

Revealing Cropping Intensity Dynamics Using High-Resolution Imagery: A Case Study in Shaanxi Province, China

by Yadong Liu, Hongmei Li, Lin Zhu, Bin Chen, Meirong Li, Huijuan He, Hui Zhou, Zhao Wang and Qiang Yu

Remote Sens. 2024, 16(20), 3832; https://doi.org/10.3390/rs16203832 - 15 Oct 2024

Cited by 1 | Viewed by 956

Abstract

Reliable and continuous information on cropping intensity is crucial for assessing cropland utilization and formulating policies regarding cropland protection and management. However, there is still a lack of high-resolution cropping intensity maps for recent years, particularly in fragmented agricultural regions. In this study, [...] Read more.

Reliable and continuous information on cropping intensity is crucial for assessing cropland utilization and formulating policies regarding cropland protection and management. However, there is still a lack of high-resolution cropping intensity maps for recent years, particularly in fragmented agricultural regions. In this study, we combined Landsat-8 and Sentinel-2 imagery to generate cropping intensity maps from 2019 to 2023 at a 10 m resolution for Shaanxi Province, China. First, the satellite imagery was harmonized to construct 10-day composite enhanced vegetation index (EVI) time series. Then, the cropping intensity was determined by counting the number of valid EVI peaks within a year. Assessment based on 578 sample points showed a high level of accuracy, with overall accuracy and Kappa coefficient values exceeding 0.96 and 0.93, respectively. We further analyzed the spatiotemporal patterns of cropping intensity and generated a map of abandoned cropland in Shaanxi. The results indicated that cropland in Shaanxi Province was mainly utilized for single-cropping (52.9% of area), followed by double-cropping (35.2%), with non-cropping accounting for 11.9%. Cropping intensity tended to be lower in the north and higher in the south. Temporally, the average cropping intensity of Shaanxi increased from 1.1 to over 1.3 from 2019 to 2023. Despite this upward trend, large areas of cropland were abandoned in northern Shaanxi. These results demonstrate the potential of utilizing Landsat-8 and Sentinel-2 imagery to identify cropping intensity dynamics in fragmented agricultural regions and to guide more efficient cropland management. Full article

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

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31 pages, 21167 KiB

Open AccessArticle

Assessing Polarisation of Climate Phenomena Based on Long-Term Precipitation and Temperature Sequences

by Bernard Twaróg

Sustainability 2024, 16(19), 8311; https://doi.org/10.3390/su16198311 - 24 Sep 2024

Cited by 1 | Viewed by 1663

Abstract

This article presents an analysis of monthly precipitation totals based on data from the Global Precipitation Climatology Centre and monthly mean temperatures from the National Oceanic and Atmospheric Administration for 377 catchments located worldwide. The data sequences, spanning 110 years from 1901 to [...] Read more.

This article presents an analysis of monthly precipitation totals based on data from the Global Precipitation Climatology Centre and monthly mean temperatures from the National Oceanic and Atmospheric Administration for 377 catchments located worldwide. The data sequences, spanning 110 years from 1901 to 2010, are analysed. These long-term precipitation and temperature sequences are used to assess the variability in climate characteristics, referred to here as polarisation. This article discusses the measures of polarisation used in the natural sciences. This study adopts two measures to evaluate the phenomenon of polarisation. The first measure is defined based on a stationary time series, calculated as the ratio of the amplitude of values to the standard deviation. The second measure is proposed as the difference in trends of these values. Based on the analysis of monthly precipitation data in the studied catchments, polarisation components are confirmed in 25% of the cases, while in the remaining 75%, they are not. For temperature data, polarisation is confirmed in 12.2% of the cases and not in the remaining 88.8%. The trend analysis employs Mann–Kendall tests at a 5% significance level. The Pettitt test is used to determine the point of trend change for precipitation and temperature data. This article underscores the complex relationship between climate polarisation and sustainable development, reaffirming that sustainable development cannot be pursued in isolation from the challenges posed by climate change. It emphasises the importance of integrating environmental, social, and economic strategies to adapt to extreme climatic events and mitigate their effects. This research is supported by detailed graphical analyses, with the results presented in tabular form. Full article

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

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17 pages, 688 KiB

Open AccessArticle

Assessing Heatwave-Related Deaths among Older Adults by Diagnosis and Urban/Rural Areas from 1999 to 2020 in Slovenia

by Simona Perčič, Katarina Bitenc, Majda Pohar, Anka Uršič, Tanja Cegnar and Ana Hojs

Climate 2024, 12(9), 148; https://doi.org/10.3390/cli12090148 - 21 Sep 2024

Cited by 1 | Viewed by 1355

Abstract

Background: The association between mortality and heatwaves is well documented. Heatwaves frequency, intensity, and duration increase with global climate change. The most vulnerable group for dying during heatwaves is older people. Knowing which diseases contribute to a higher number of deaths during heatwaves [...] Read more.

Background: The association between mortality and heatwaves is well documented. Heatwaves frequency, intensity, and duration increase with global climate change. The most vulnerable group for dying during heatwaves is older people. Knowing which diseases contribute to a higher number of deaths during heatwaves is important for planning appropriate public health preventive measures. Methods: We assessed the short-term association between the number of deaths for older adults (75+ years) and heatwaves in the years 1999 to 2020 in Slovenia. We estimated the relative risks (RR) with a 95% confidence interval for the number of deaths for the observed diagnosis (all causes, circulatory, respiratory) and urban vs. rural areas associated with heatwaves in Slovenia for each year, comparing the number of deaths during heatwaves with reference days. Results: Most years showed no significant increase in deaths during heatwaves for those aged 75 and older. However, in 2006, 2007, 2014, and 2015, there was a significant increase in deaths during heatwaves. For the general population, heatwaves were associated with an increase in deaths due to all causes: 10% more in 2006 and 26% more in both 2007 and 2014. For those aged 75 and older, heatwaves were associated with an increase in deaths due to all causes: 22% more in 2007, 27% more in 2014, and 28% more in 2015. For those aged 75 and older, heatwaves were associated with an increase in deaths due to circulatory system diseases: 25% more in 2006, 33% more in 2007, 30% more in 2014, and 27% more in 2015. Regarding urban vs. rural areas, in 2006 and 2012, the elderly in urban areas were more affected, with 33% and 26% more deaths, respectively. In contrast, in 2007, 2014, and 2015, old age population in rural areas was more affected, with 29%, 26%, and 31% more deaths, respectively. Conclusions: According to the literature data, older adults are most susceptible to the effects of extreme heat due to physiological changes that occur with aging, chronic diseases, certain medications, a sedentary lifestyle, and social isolation. The results of our study will help in planning appropriate preventive public health measures to better protect older adults during the next heatwaves in Slovenia. Full article

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

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21 pages, 1952 KiB

Open AccessArticle

A Farmer-Centric Cost–Benefit Analysis of Climate-Smart Agriculture in the Gandaki River Basin of Nepal

by Shobha Poudel, Rabin Thapa and Bhogendra Mishra

Climate 2024, 12(9), 145; https://doi.org/10.3390/cli12090145 - 16 Sep 2024

Cited by 2 | Viewed by 2844

Abstract

Climate-smart agriculture (CSA) is a climate-resilient practice that stands out globally as an important practice through which we can deal with emerging challenges through adaptation and mitigation to increase crop productivity and resilience. Despite its significance, a comprehensive cost–benefit analysis of the adoption [...] Read more.

Climate-smart agriculture (CSA) is a climate-resilient practice that stands out globally as an important practice through which we can deal with emerging challenges through adaptation and mitigation to increase crop productivity and resilience. Despite its significance, a comprehensive cost–benefit analysis of the adoption of these practices has not yet been carried out. This study aims to bridge the knowledge gap between the cost and effectiveness of CSA practices adopted by small-scale farmers in growing rice, wheat and maize, the most staple crops in the Gandaki River Basin of Nepal. In this study, net present value (NPV), internal rate of return (IRR), benefit–cost (BC) ratio, net benefit investment (NK) ratio and payback period, along with the value of externalities (social and environmental), were employed to assess the profitability of CSA practices. The findings indicate that almost all the CSA practices analyzed were profitable, with the exception of solar water management in maize with very low IRR (6%) and a longer payback period. The outcome of this study offers valuable insights for farmers in choosing profitable CSA technology and for policy makers in promoting better CSA technology, upscaling CSA practices, and formulating new agricultural policies and programs in the context of the changing climate. Full article

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

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19 pages, 9113 KiB

Open AccessArticle

Causes of Increased Compound Temperature and Precipitation Extreme Events in the Arid Region of Northwest China from 1961 to 2100

by Huihui Niu, Weijun Sun, Baojuan Huai, Yuzhe Wang, Rensheng Chen, Chuntan Han, Yingshan Wang, Jiaying Zhou and Lei Wang

Remote Sens. 2024, 16(17), 3111; https://doi.org/10.3390/rs16173111 - 23 Aug 2024

Cited by 1 | Viewed by 1732

Abstract

Compound extreme events pose more grave threats to human health, the natural environment, and socioeconomic systems than do individual extreme events. However, the drivers and spatiotemporal change characteristics of compound extreme events under climate transition remain poorly understood, especially in the arid region [...] Read more.

Compound extreme events pose more grave threats to human health, the natural environment, and socioeconomic systems than do individual extreme events. However, the drivers and spatiotemporal change characteristics of compound extreme events under climate transition remain poorly understood, especially in the arid region of Northwest China. This study examined the spatiotemporal change characteristics and driving mechanisms of extreme temperature and precipitation compound events in Northwest China based on data from 86 national meteorological stations and 11 climate models of the Coupled Model Intercomparison Project, Phase 6. The results indicated that (1) the frequency values of heat extremity–dry (1.60/10a) and heat extremity–heavy precipitation (0.60/10a) events increased from 1961 to 2020, and showed a faster uptrend after 1990 than before. (2) Under four shared socioeconomic pathway scenarios, there is also the likelihood of an upward trend in heat extremity–dry and heat extremity–heavy precipitation events in Northwest China by the end of 21 century, especially under SSP585, with probability values of 1.70/10a and 1.00/10a, respectively. (3) A soil moisture deficit leads to decreased evaporation and increased sensible heat by reduction in the soil–atmosphere exchange; the non-adiabatic heating process leads to a higher frequency of hot days. This land–air interaction feedback mechanism is a significant driver of heat extremity–dry events in Northwest China. (4) In the Northwest China region, the warmer trend surpasses the wetter trend, contributing to increased specific humidity, and the vapor pressure deficit may lead to an increasing frequency of extreme precipitation, consequently increasing heat extremity–heavy precipitation events. These results provide new insights for the understanding of compound extreme events, in order to cope with their risks. Full article

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

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18 pages, 1212 KiB

Open AccessArticle

Predictive Analysis of Adaptation to Drought of Farmers in the Central Zone of Colombia

by Jorge Armando Hernández-López, Diana Ximena Puerta-Cortés and Hernán J. Andrade

Sustainability 2024, 16(16), 7210; https://doi.org/10.3390/su16167210 - 22 Aug 2024

Cited by 2 | Viewed by 1435

Abstract

Drought constitutes one of the natural phenomena that causes the greatest socio-economic, and environmental losses in both the short and long term worldwide. Each year, these events are related to the presence of “El Niño—Southern Oscillation” (ENSO), which occurs throughout Colombia and has [...] Read more.

Drought constitutes one of the natural phenomena that causes the greatest socio-economic, and environmental losses in both the short and long term worldwide. Each year, these events are related to the presence of “El Niño—Southern Oscillation” (ENSO), which occurs throughout Colombia and has serious consequences in the agricultural and food sectors, as well as in most of the country’s population. Farmers have adopted a number of strategies to mitigate the negative impact of droughts on food production. Certainly, when implementing future strategies, such strategies will be less effective if farmers’ insights on ENSO are not considered. Consequently, this study was carried out to analyze the variables that predict adaptation to droughts in the dry zones of the department of Tolima. Three questionnaires were designed: socioeconomic vulnerability (SVT), risk perception (SRPT) and drought adaptation (SAT). A non-probability sample of 538 farmers was surveyed. Socio-economic vulnerability and drought perception were found to be predictive of drought adaptation in the study sample, and older people were found to be resilient to adaptation. The results of this research provide empirical evidence to analyze and formulate public policies about the impact of droughts on the most vulnerable populations. Full article

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

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18 pages, 1171 KiB

Open AccessArticle

Adaptation and Coping Strategies of Women to Reduce Food Insecurity in an Era of Climate Change: A Case of Chireya District, Zimbabwe

by Everjoy Magwegwe, Taruberekerwa Zivengwa and Mashford Zenda

Climate 2024, 12(8), 126; https://doi.org/10.3390/cli12080126 - 22 Aug 2024

Cited by 6 | Viewed by 2841

Abstract

The research investigated how women employ various adaptation and coping mechanisms to alleviate food insecurity resulting from the impacts of climate change. The documentation of the debate on the role of women in adaptation and coping with climate change is relatively limited. Climate [...] Read more.

The research investigated how women employ various adaptation and coping mechanisms to alleviate food insecurity resulting from the impacts of climate change. The documentation of the debate on the role of women in adaptation and coping with climate change is relatively limited. Climate change’s effect on food security in semi-arid areas could potentially increase the population of individuals residing in severe poverty. Over the past three decades, Africa’s sub-tropics have experienced irregular rainfall and prolonged droughts, which have negatively affected agriculture and food production. This research utilized a combination of qualitative and quantitative approaches within a mixed-method design, guided by the pragmatic paradigm. Based on the results of the study, water harvesting/dam construction and income generating projects (IGPs) were identified as the most effective coping strategies for women. This study recommends implementing awareness campaigns to educate women farmers about the negative effects of climate change and the need for integrated and comprehensive capacity-building frameworks. By understanding the challenges women face in adapting to and coping with climate change, it is hoped that more effective and sustainable solutions can be developed. Full article

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

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20 pages, 1305 KiB

Open AccessArticle

Analysis of the Impact of the Digital Economy on Carbon Emission Reduction and Its Spatial Spillover Effect—The Case of Eastern Coastal Cities in China

by Juanjuan Zhong, Ye Duan, Caizhi Sun and Hongye Wang

ISPRS Int. J. Geo-Inf. 2024, 13(8), 293; https://doi.org/10.3390/ijgi13080293 - 18 Aug 2024

Cited by 1 | Viewed by 1422

Abstract

The expansion of the digital economy is crucial for halting climate change, as carbon emissions from urban energy use contribute significantly to global warming. This study uses the Difference-in-Differences Model and the Spatial Durbin Model determine whether the digital economy may support the [...] Read more.

The expansion of the digital economy is crucial for halting climate change, as carbon emissions from urban energy use contribute significantly to global warming. This study uses the Difference-in-Differences Model and the Spatial Durbin Model determine whether the digital economy may support the development of reducing carbon emissions and its geographic spillover effects in Chinese cities on the east coast. In addition, it looks more closely at the effects of lowering carbon emissions in space by separating them into direct, indirect, and spatial impact parts. The findings show that (1) from 2012 to 2021, the digital economy favored carbon emission reductions in China’s eastern coastline cities, as supported by the robustness test. (2) The link between digital economy growth and carbon emissions is highly variable, with smart city development and urban agglomeration expansion both cutting city carbon emissions considerably. Successful digital economy strategies can lower CO₂ emissions from nearby cities. (3) Eastern coastal cities have a considerable spatial spillover impact, and the digital economy mitigates local energy consumption and carbon emissions while simultaneously enhancing environmental quality in nearby urban areas. This analysis proposes that the peak carbon and carbon neutrality targets can be met by increasing the digital economy and enhancing regional environmental governance cooperation. Full article

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

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18 pages, 1635 KiB

Open AccessEditor’s ChoiceArticle

Interpolation of Nitrogen Fertilizer Use in Canada from Fertilizer Use Surveys

by James Arthur Dyer, Angela Pearson and Raymond Louis Desjardins

Agronomy 2024, 14(8), 1700; https://doi.org/10.3390/agronomy14081700 - 1 Aug 2024

Viewed by 1246

Abstract

Canadian nitrogen (N) fertilizer use has more than doubled since 1990 (1.2 to 2.9 MtN by 2021). Consequently, a better understanding of this trend is needed. A comprehensive set of recommended N rates (RNRs) that agreed with the fertilizer sales data from 1996 [...] Read more.

Canadian nitrogen (N) fertilizer use has more than doubled since 1990 (1.2 to 2.9 MtN by 2021). Consequently, a better understanding of this trend is needed. A comprehensive set of recommended N rates (RNRs) that agreed with the fertilizer sales data from 1996 and 2001 was compared with the Fertilizer Use Survey (FUS). The FUS was conducted from 2014 to 2021, with 2017 being the most representative year for these data. Using non-parametric statistics, confidence intervals were derived from the histograms used to present the FUS data. N application rates from the RNR for canola, spring and Duram wheat, and oats in the west were all below their respective FUS confidence intervals, whereas N application rates for grain corn showed almost no difference in N use between the RNR and FUS. Crop-specific N application rates interpolated from the RNR and FUS were integrated over their respective crop areas and plotted against national fertilizer sales records from 1990 to 2021. The rapid increase in N use between 2001 and 2017 (0.89 MtN), 90% of it (0.80 MtN) in Western Canada, was primarily due to the increased application rates per crop, rather than crop area changes. The RNR-FUS interpolations were a good approximation of N sales records and could improve farm GHG emissions modelling. The economically important crops in Western Canada should be the main focus for N-related GHG reduction measures, but production losses need to be avoided. Full article

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

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29 pages, 6065 KiB

Open AccessArticle

Challenges to Viticulture in Montenegro under Climate Change

by António Fernandes, Nataša Kovač, Hélder Fraga, André Fonseca, Sanja Šućur Radonjić, Marko Simeunović, Kruna Ratković, Christoph Menz, Sergi Costafreda-Aumedes and João A. Santos

ISPRS Int. J. Geo-Inf. 2024, 13(8), 270; https://doi.org/10.3390/ijgi13080270 - 30 Jul 2024

Cited by 2 | Viewed by 1574

Abstract

The Montenegrin climate is characterised as very heterogeneous due to its complex topography. The viticultural heritage, dating back to before the Roman empire, is settled in a Mediterranean climate region, located south of the capital Podgorica, where climate conditions favour red wine production. [...] Read more.

The Montenegrin climate is characterised as very heterogeneous due to its complex topography. The viticultural heritage, dating back to before the Roman empire, is settled in a Mediterranean climate region, located south of the capital Podgorica, where climate conditions favour red wine production. However, an overall increase in warmer and drier periods affects traditional viticulture. The present study aims to discuss climate change impacts on Montenegrin viticulture. Bioclimatic indices, ensembled from five climate models, were analysed for both historical (1981–2010) and future (2041–2070) periods upon three socio-economic pathways: SSP1-2.6, SSP3-7.0 and SSP5-8.5. CHELSA (≈1 km) was the selected dataset for this analysis. Obtained results for all scenarios have shown the suppression of baseline conditions for viticulture. The average summer temperature might reach around 29.5 °C, and the growing season average temperature could become higher than 23.5 °C, advancing phenological events. The Winkler index is estimated to range from 2900 °C up to 3100 °C, which is too hot for viticulture. Montenegrin viticulture requires the application of adaptation measures focused on reducing temperature-increase impacts. The implementation of adaptation measures shall start in the coming years, to assure the lasting productivity and sustainability of viticulture. Full article

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

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18 pages, 4430 KiB

Open AccessArticle

Repeated Mild Summer Drought in Crataegus monogyna Jacq. Provokes Compensation Growth in the Following Year

by Kristine Vander Mijnsbrugge, Stefaan Moreels, Laura Decorte, Marie Stessens and Eduardo Notivol Paino

Forests 2024, 15(7), 1234; https://doi.org/10.3390/f15071234 - 16 Jul 2024

Cited by 1 | Viewed by 966

Abstract

Water limitations will pose significant challenges to forest ecosystems across Europe. To gain a deeper understanding of the potential impacts, we investigated the response of the common shrub Crataegus monogyna to two summer droughts, each followed by rewatering. The experimental design consisted of [...] Read more.

Water limitations will pose significant challenges to forest ecosystems across Europe. To gain a deeper understanding of the potential impacts, we investigated the response of the common shrub Crataegus monogyna to two summer droughts, each followed by rewatering. The experimental design consisted of a common garden with potted saplings from a local Belgian (n = 48), a Swedish (n = 47), and a Spanish-Pyrenean provenance (n = 48). We quantified the effects on growth and leaf phenology, focusing on the legacies in the year following the droughts. Responses were influenced by the severity of the drought and by its timing. Most strikingly, height increment was enhanced by 24% (p = 0.046) in comparison to the controls in the year following the droughts in the group of plants that endured the two drought treatments, each time without developing visible stress symptoms. Only one such mild drought, whether early or late summer, did not lead to this response, suggesting stress memory acting as a growth promoter. A late summer drought that resulted in visible drought symptoms led to a reduced diameter increment in the year following the droughts, independent of the preceding treatment (severe, mild, or no drought), whereas this was not the case for a similar drought in early summer. Minor leaf phenological responses were detected in the year following the droughts. Finally, the non-local provenances did not respond in a deviating way to the droughts compared to the local provenance. Our findings contribute to the prediction of carbon sequestration in forests and other woody vegetations in the temperate regions of Europe. Full article

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

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18 pages, 4476 KiB

Open AccessArticle

Flood Risk Assessment for Sustainable Transportation Planning and Development under Climate Change: A GIS-Based Comparative Analysis of CMIP6 Scenarios

by Muamer Abuzwidah, Ahmed Elawady, Ayat Gamal Ashour, Abdullah Gokhan Yilmaz, Abdallah Shanableh and Waleed Zeiada

Sustainability 2024, 16(14), 5939; https://doi.org/10.3390/su16145939 - 12 Jul 2024

Cited by 1 | Viewed by 2360

Abstract

Climate change is causing a range of environmental impacts, including increased flood frequency and intensity, posing significant risks to human populations and transportation infrastructure. Assessing flood risk under climate change is critical, but it is challenging due to uncertainties associated with climate projections [...] Read more.

Climate change is causing a range of environmental impacts, including increased flood frequency and intensity, posing significant risks to human populations and transportation infrastructure. Assessing flood risk under climate change is critical, but it is challenging due to uncertainties associated with climate projections and the need to consider the interactions between different factors that influence flood risk. Geographic Information Systems (GISs) are powerful tools that can be used to assess flood risk under climate change by gathering and integrating a range of data types and sources to create detailed maps of flood-prone areas. The primary goal of this research is to create a comprehensive GIS-based flood risk map that includes various climate change scenarios derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6) models. This goal will leverage the Analytic Hierarchy Process (AHP) methodology to better understand the impacts of these climate change scenarios on the transportation network. Furthermore, this study aims to evaluate the existing flood risk map and assess the potential impacts of prospective climate scenarios on the levels of flood risk. The results showed that the northern and coastal regions of the United Arab Emirates (UAE) are at higher risk of flooding, with the majority of the population living in these areas. The projections for future flood risk levels indicate that under the SSP245 scenario, flood risk levels will generally be low, but some areas in the northern and eastern regions of the UAE may still face high to very high flood risk levels due to extensive urbanization and low-lying coastal regions. Under the SSP585 scenario, flood risk levels are projected to be significantly higher, with a widespread distribution of very high and high flood risk levels across the study area, leading to severe damage to infrastructure, property, and human lives. The recent publication of the CMIP6 models marks a significant advancement, and according to the authors’ knowledge, there have been no studies that have yet explored the application of CMIP6 scenarios. Consequently, the insights provided by this study are poised to be exceptionally beneficial to researchers globally, underscoring the urgent necessity for holistic sustainable flood risk management approaches for geography, planning, and development areas. These approaches should integrate both sustainable transportation infrastructure development and risk mitigation strategies to effectively address the anticipated impacts of flooding events within the study region. Full article

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

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12 pages, 2154 KiB

Open AccessArticle

Effects of Warming and Increased Precipitation on Root Production and Turnover of Stipa breviflora Community in Desert Steppe

by Qi Li, Jianying Guo, Zhanyi Wang, Chengjie Wang, Pengbo Liu, Guangyi Lv, Zhenqi Yang, Chunjie Wang and Xiao Qiu

Agronomy 2024, 14(7), 1521; https://doi.org/10.3390/agronomy14071521 - 12 Jul 2024

Viewed by 885

Abstract

Organic carbon in grassland mainly exists in the soil, and root production and turnover play important roles in carbon input into the soil. However, the effects of climate change on plant root dynamics in desert steppe are unknown. We conducted an experiment in [...] Read more.

Organic carbon in grassland mainly exists in the soil, and root production and turnover play important roles in carbon input into the soil. However, the effects of climate change on plant root dynamics in desert steppe are unknown. We conducted an experiment in a desert steppe, which included ambient temperature (T0); temperature increased by 2 °C (T1); temperature increased by 4 °C (T2); natural precipitation (P0); precipitation increased by 25% (P1); precipitation increased by 50% (P2); and the interaction between warming and increased precipitation. Plant community aboveground characteristics; root production; and root turnover were measured. We found that the root length production of the T0P2; T1P1; T2P0; and T2P1 treatments were significantly higher than that of the T0P0 treatment, with an increment of 98.70%, 11.72%, 163.03%, and 85.14%, respectively. Three treatments with temperature increased by 2 °C (T1P0; T1P1; and T1P2) and significantly increased root turnover rate compared to the T0P0 treatment, with increases of 62.53%, 42.57%, and 35.55%, respectively. The interaction between warming and increased precipitation significantly affected the root production of the community (p < 0.01), but this interaction was non-additive. Future climate warming will benefit the accumulation of root-derived carbon in desert steppe communities. Full article

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

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19 pages, 6338 KiB

Open AccessArticle

Small Municipalities in the Amazon under the Risk of Future Climate Change

by Everaldo B. de Souza, Brenda C. S. Silva, Emilene M. F. Serra, Melgris J. Becerra Ruiz, Alan C. Cunha, Paulo J. P. O. Souza, Luciano P. Pezzi, Edson J. P. da Rocha, Adriano M. L. Sousa, João de Athaydes Silva, Jr., Alexandre M. C. do Carmo, Douglas B. S. Ferreira, Aline M. M. Lima, Flavio A. A dos Santos, Bergson C. Moraes, Maria de L. P. Ruivo, Peter M. Toledo and Tercio Ambrizzi

Climate 2024, 12(7), 95; https://doi.org/10.3390/cli12070095 - 29 Jun 2024

Cited by 5 | Viewed by 2212

Abstract

The focus of this work is on small municipalities (population below 50 thousand inhabitants) that cover around 87% of the territory of the Brazilian Legal Amazon (BLA). Based on a comprehensive integrated analysis approach using the three components hazard (climate extremes from CMIP6 [...] Read more.

The focus of this work is on small municipalities (population below 50 thousand inhabitants) that cover around 87% of the territory of the Brazilian Legal Amazon (BLA). Based on a comprehensive integrated analysis approach using the three components hazard (climate extremes from CMIP6 future scenarios), exposure (directly affected population), and vulnerability (subdimensions of susceptibility and coping/adaptive capacity by using multidimensional indicators), the latter two using current datasets provided by the official Census IBGE 2022, we document a quantitative assessment of the risk R of natural disasters in the BLA region. We evidenced a worrying and imminent intensification of the curve of R in most Amazonian municipalities over the next two 25-year periods. The overall results of the highest proportions of R (total municipalities affected) pointed out the Amazonas, Roraima, Pará, and Maranhão as the main states, presenting projected categories of R high in the near future (2015 to 2039) and very high in the far future (2040 to 2064). The detailed assessment of the susceptibility and coping/adaptive capacity allowed us to elucidate the principal indicators that aggravate the degree of vulnerability: economy, the precariousness of urban infrastructure, medical services, communication, and urban mobility, whose combined factors, unfortunately, reveal a widespread poverty profile along the small Amazonian municipalities. Our scientific findings can assist decision makers in targeted strategies planning and public policies to minimize and mitigate ongoing and future climate change. Full article

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

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27 pages, 10897 KiB

Open AccessArticle

Historic Changes and Future Projections in Köppen–Geiger Climate Classifications in Major Wine Regions Worldwide

by Cristina Andrade, André Fonseca, João A. Santos, Benjamin Bois and Gregory V. Jones

Climate 2024, 12(7), 94; https://doi.org/10.3390/cli12070094 - 27 Jun 2024

Cited by 6 | Viewed by 2263

Abstract

A valuable tool for comprehending and characterizing climate patterns on a global scale is the Köppen–Geiger climate classification system. When it comes to wine production, the climate of a region plays an essential role in determining whether specific grape varieties can be cultivated, [...] Read more.

A valuable tool for comprehending and characterizing climate patterns on a global scale is the Köppen–Geiger climate classification system. When it comes to wine production, the climate of a region plays an essential role in determining whether specific grape varieties can be cultivated, largely determining the style of wine that can be made, and influencing the consistency of overall wine quality. In this study, the application of the Köppen–Geiger classification system to the latest Coupled Model Intercomparison Project (CMIP6) experiments has been explored. To establish a baseline for the historical period (1970–2000), the WorldClim dataset was used alongside a selection of an ensemble of 14 Global Climate Models. The evaluation of climate variability across winemaking regions is conducted by considering future climate projections from 2041 to 2060, which are based on different anthropogenic radiative forcing scenarios (Shared Socioeconomic Pathways, SSP2–4.5, and SSP5–8.5). The results are the most comprehensive documentation of both the historical climate classifications for most wine regions worldwide and the potential changes in these classifications in the future. General changes in climate types are projected to occur largely in a significant shift from a warm summer climate to a hot summer climate in temperate and dry zones worldwide (climate types C and B, respectively). This shift poses challenges for grape cultivation and wine production. The grape development process can be significantly affected by high temperatures, which could result in early ripening and changes in the grape berry’s aromatic compounds. As regions transition and experience different climates, wine producers are required to adapt their vineyard management strategies by implementing suitable measures that can effectively counter the detrimental impacts of abiotic stresses on grape quality and vineyard health. These adaptation measures may include changes in canopy and soil management, using different variety-clone-rootstock combinations, adopting irrigation methods, or shifting into other microclimatic zones, among other effective techniques. To ensure long-term sustainability, wine producers must consider the climatic change projections that are specific to their region, allowing them to make more informed decisions about vineyard management practices, reducing risks, and ultimately making the wine industry more resilient and adaptive to the ongoing effects of climate change. Full article

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

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18 pages, 2639 KiB

Open AccessArticle

Climate Change-Induced Growth Decline in Planted Forests of Quercus variabilis Blume near Beijing, China

by Ayjamal Keram, Puyuan Liu, Guolei Li, Wen Liu and Ümüt Halik

Forests 2024, 15(7), 1086; https://doi.org/10.3390/f15071086 - 22 Jun 2024

Cited by 1 | Viewed by 1495

Abstract

A progressive decline in tree growth may be induced by global warming, affecting tree health and eventually resulting in death, particularly for trees growing in rocky mountainous regions where seasonal droughts have become more pronounced. However, tree growth dynamics in areas experiencing pronounced [...] Read more.

A progressive decline in tree growth may be induced by global warming, affecting tree health and eventually resulting in death, particularly for trees growing in rocky mountainous regions where seasonal droughts have become more pronounced. However, tree growth dynamics in areas experiencing pronounced climate change have received little attention. In this study, a total of 100 (10 m × 10 m) grid plots were investigated in planted forests of Chinese cork oak (Quercus variabilis Blume), which were established in the 1960s and 1970s in a rocky mountainous area near Beijing, northern China. Furthermore, the radial growth of Q. variabilis (a total of 843 trees sampled from the dominant [D], co-dominant [CD], and suppressed [S] crown classes) was analyzed using retrospective dendrochronology and generalized additive models. The effects of meteorological changes between 1962 and 2020 on radial growth across the three crown classes were examined using correlation analysis. The results indicated that the growth of Q. variabilis initially increased and then decreased after 2010 at the regional level, and these trends varied according to crown class. The radial growth of the D trees responded more positively to an increase in temperature and drought severity index (<0 for dry and >0 for wet conditions) compared with that of the CD and S trees. The growth of the D and CD trees continuously increased under higher temperatures during the rainy seasons (June to September); however, the increases were higher for D than for CD trees. In contrast, the radial growth of S trees declined. We confirmed the historical effects of rising temperatures on tree growth and health, which are linked to water availability. Our data suggested that Q. variabilis trees will be considerably affected by intensified droughts. This study furthers our knowledge regarding the impact of climate change on tree and forest growth and provides management strategies for afforestation projects in rocky mountainous areas that are facing climate change. Full article

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

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22 pages, 4205 KiB

Open AccessArticle

Sustainable Geoinformatic Approaches to Insurance for Small-Scale Farmers in Colombia

by Ahmad Abd Rabuh, Richard M. Teeuw, Doyle Ray Oakey, Athanasios V. Argyriou, Max Foxley-Marrable and Alan Wilkins

Sustainability 2024, 16(12), 5104; https://doi.org/10.3390/su16125104 - 15 Jun 2024

Cited by 1 | Viewed by 1570

Abstract

This article presents a low-cost insurance system developed for smallholder farms in disaster-prone regions, primarily using free Earth observation (EO) data and free open source software’s (FOSS), collectively termed “sustainable geoinformatics.” The study examined 30 farms in Risaralda Department, Colombia. A digital elevation [...] Read more.

This article presents a low-cost insurance system developed for smallholder farms in disaster-prone regions, primarily using free Earth observation (EO) data and free open source software’s (FOSS), collectively termed “sustainable geoinformatics.” The study examined 30 farms in Risaralda Department, Colombia. A digital elevation model (12.5 m pixels) from the ALOS PALSAR satellite sensor was used with a geographic information system (GIS) to map the terrain, drainage, and geohazards of each farming district. Google Earth Engine (GEE) was used to carry out time-series analysis of 15 EO and weather datasets for 1998 to 2020. This analysis enabled the levels of risk from hydrometeorological hazards to be determined for each farm of the study, providing key data for the setting of insurance premiums. A parametric insurance product was developed using a proprietary mobile phone app that collected GPS-tagged, time-stamped mobile phone photos to verify crop damage, with further verification of crop health also provided by daily near-real-time satellite imagery (e.g., PlanetScope with 3 m pixels). Machine learning was used for feature identification with the photos and the satellite imagery. Key features of this insurance system are its low operational cost and rapid damage verification relative to conventional approaches to farm insurance. This relatively fast, low-cost, and affordable approach to insurance for small-scale farming enhances sustainable development by enabling policyholder farmers to recover more quickly from disasters. Full article

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

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19 pages, 4487 KiB

Open AccessArticle

Enhancing Seasonal PM2.5 Estimations in China through Terrain–Wind–Rained Index (TWRI): A Geographically Weighted Regression Approach

by Boqi Peng, Busheng Xie, Wei Wang and Lixin Wu

Remote Sens. 2024, 16(12), 2145; https://doi.org/10.3390/rs16122145 - 13 Jun 2024

Cited by 3 | Viewed by 1019

Abstract

PM2.5 concentrations, closely linked to human health, are significantly influenced by meteorological and topographical factors. This study introduces the Terrain–Wind–Rain Index (TWRI), a novel index that integrates the Terrain–Wind Closed Index (TWCI) with relative humidity to quantitatively examine the coupling effect of natural [...] Read more.

PM2.5 concentrations, closely linked to human health, are significantly influenced by meteorological and topographical factors. This study introduces the Terrain–Wind–Rain Index (TWRI), a novel index that integrates the Terrain–Wind Closed Index (TWCI) with relative humidity to quantitatively examine the coupling effect of natural elements on PM2.5 concentration and its application to PM2.5 inversion. By employing Geographically Weighted Regression (GWR) models, this study evaluates the inversion results of PM2.5 concentrations using TWRI as a factor. Results reveal that the annual average correlation between TWRI and site-measured PM2.5 concentrations increased from 0.65 to 0.71 compared to TWCI. Correlations improved across all seasons, with the most significant enhancement occurring in summer, from 0.51 to 0.66. On the inversion results of PM2.5, integrating TWRI into traditional models boosted accuracy by 1.3%, 5.4%, 4%, and 7.9% across four seasons, primarily due to the varying correlation between TWRI and PM2.5. Furthermore, the inversion results of coupled TWRI more effectively highlight the high value areas in closed areas and the low value areas in humid areas. Full article

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

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21 pages, 7330 KiB

Open AccessArticle

Dry–Wet Changes in a Typical Agriculture and Pasture Ecotone in China between 1540 and 2019

by Xiaodong Wang, Yujia Song, Yu An, Xiaohui Liu and Xiaoqiang Li

ISPRS Int. J. Geo-Inf. 2024, 13(6), 191; https://doi.org/10.3390/ijgi13060191 - 7 Jun 2024

Viewed by 1254

Abstract

Exploring periodic dry–wet changes is an important topic in climate change research due to its impact on drought and flood disasters. The purpose of this research was to determine the occurrence law of dry–wet changes in China on a scale of several hundred [...] Read more.

Exploring periodic dry–wet changes is an important topic in climate change research due to its impact on drought and flood disasters. The purpose of this research was to determine the occurrence law of dry–wet changes in China on a scale of several hundred years, using the example of transitional zones. In this study, we analyzed typical areas of the ecotone between agricultural land and pasture along the Great Wall of China. The ring width index of Carya cathayensis was fitted with the March–August Palmer drought severity index (PDSI₃₈). The PDSI₃₈ was divided into different periods using the stepwise function fitting method. The results indicated that there were two dry periods and one wet period in the region from 1543 to 2019. In each dry and wet period, there were also different temporal periods, including long (decades), intermediate (ten years), and short periods (several years). Drought represents a significant threat to agricultural production in China. In the first dry period (1543–1756), four periods with low PDSI₃₈ values (1633–1635, PDSI₃₈ = −1.71; 1636–1939, PDSI₃₈ = −3.35; 1640–1642, PDSI₃₈ = −4.68; and 1643–1645, PDSI₃₈ = −2.92) occurred, during which severe droughts (PDSI₃₈ < −4) lasted for 13 years. The dry–wet change showed the characteristics of a 12-year or multiple 12-year cycle. The results can be used to prepare to effectively address extreme drought scenarios worldwide in the future. Full article

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

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16 pages, 4711 KiB

Open AccessArticle

Potential of Modified Reduced Tillage with Cover/Green Manure Crop for Climate Change Mitigation in a Smallholder Rainfed Farming System

by Nabeeha Javed, Shahzada Sohail Ijaz, Qaiser Hussain, Muhammad Ansar, Abdulwahed Fahad Alrefaei, Bader O. Almutairi, Wajid Zaman and Munazza Yousra

Sustainability 2024, 16(11), 4781; https://doi.org/10.3390/su16114781 - 4 Jun 2024

Viewed by 1625

Abstract

Soil can function as a reservoir and a source of greenhouse gases (GHGs), contingent on its management. This study assesses the potential of a modified reduced tillage (MRT) approach involving the use of cover or green manure crops as a substitute for crop [...] Read more.

Soil can function as a reservoir and a source of greenhouse gases (GHGs), contingent on its management. This study assesses the potential of a modified reduced tillage (MRT) approach involving the use of cover or green manure crops as a substitute for crop residues to mitigate GHG emissions from soil within smallholder rainfed farming systems. A two-year field experiment with different tillage techniques (moldboard plow, tine cultivator, and modified reduced tillage) and crop rotations (summer fallow–wheat and cover/green manure–wheat) was conducted at Rawalpindi, Pakistan. The results showed that MRT reduced carbon dioxide (CO₂) and nitrous oxide (N₂O) emissions by 8% and 15.3%, respectively, from soil while maintaining consistently higher soil moisture than conventional tillage techniques. The modified reduced tillage reduced the global warming potential (GWP) and greenhouse gas intensity (GHGI) by 15.8% and 20.7%, respectively. The net ecosystem exchange (NEE) was unaffected by the tillage systems. Therefore, adopting the MRT technique and incorporating green manure is a viable strategy for curtailing GHG emissions from soil, particularly in the context of smallholder rainfed farming systems. Extended, multi-year studies under various climate scenarios and agronomic practices are needed to understand the long-term impacts of MRT and crop rotations on GHG emissions. Full article

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

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17 pages, 2129 KiB

Open AccessArticle

Urban Vulnerability under the Extreme High Temperatures in the Chengdu-Chongqing Area, Western China

by Zhaoqi Yin, Weipeng Li, Zhongsheng Chen, Li Zhu and Panheng Shui

Sustainability 2024, 16(11), 4749; https://doi.org/10.3390/su16114749 - 3 Jun 2024

Cited by 1 | Viewed by 1373

Abstract

The frequent occurrence of extreme high-temperature events in the summer under global climate change poses a serious threat to Chinese society. An urban vulnerability evaluation system for counties in the Chengdu-Chongqing Area was constructed to calculate the urban vulnerability and distribution characteristics of [...] Read more.

The frequent occurrence of extreme high-temperature events in the summer under global climate change poses a serious threat to Chinese society. An urban vulnerability evaluation system for counties in the Chengdu-Chongqing Area was constructed to calculate the urban vulnerability and distribution characteristics of each district. In this study, a vulnerability-contribution model was used to analyze the types of urban vulnerability in the Chengdu-Chongqing Area. Additionally, combined with the optimal parameter geographic detector (OPGD) model, the main influencing factors and interactions of urban vulnerability were explored. The results show that: ① The urban vulnerability of the Chengdu-Chongqing Area is high in the east and low in the west, with vulnerability degree mostly below the medium degree. ② Exposure contributes more than 50% to severe and general urban vulnerability in the region, while adaptability contributes the highest proportion to mild urban vulnerability, reaching 47.53%. ③ From the factor perspective, the impact ratio of high-temperature days on urban vulnerability is 39.1%, and the interaction between various meteorological factors and social factors produces an enhancement effect, with the highest interaction q-value reaching 0.7863. Full article

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

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22 pages, 2803 KiB

Open AccessArticle

Assessment of the Vulnerability of Households Led by Men and Women to the Impacts of Climate-Related Natural Disasters in the Coastal Areas of Myanmar and Vietnam

by Aung Tun Oo, Ame Cho and Dao Duy Minh

Climate 2024, 12(6), 82; https://doi.org/10.3390/cli12060082 - 2 Jun 2024

Cited by 3 | Viewed by 2264

Abstract

Farm households along the coastlines of Myanmar and Vietnam are becoming increasingly vulnerable to flooding, saltwater intrusion, and rising sea levels. There is little information available on the relative vulnerability of men- and women-headed households, and the governments of Myanmar and Vietnam have [...] Read more.

Farm households along the coastlines of Myanmar and Vietnam are becoming increasingly vulnerable to flooding, saltwater intrusion, and rising sea levels. There is little information available on the relative vulnerability of men- and women-headed households, and the governments of Myanmar and Vietnam have not identified or implemented any adaptive measures aimed specifically at vulnerable peoples. This study aims to fill these gaps and assess the relative climate change vulnerability of men- and women-headed farm households. This study considers 599 farm households from two regions of Myanmar and 300 households from Thua Thien Hue province of Vietnam for the period 2021–2022. We offer a livelihood vulnerability index (LVI) analysis of men- and women-headed farm households using 46 indicators arranged into seven major components. The aggregate LVI scores indicate that farm households in Myanmar are more vulnerable (scores of 0.459 for men and 0.476 for women) to climate-related natural disasters than farm households in Vietnam (scores of 0.288 for men and 0.292 for women), regardless of the gender of the head of household. Total vulnerability indexing scores indicate that women-headed households are more vulnerable than men-headed households in both countries. Poor adaptive capacity and highly sensitive LVI dimensional scores explain the greater vulnerability of women-headed farm households. The findings also highlight the importance of the adaptive capacity components reflected in the LVI analysis in reducing farm households’ vulnerability. Full article

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

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15 pages, 5159 KiB

Open AccessTechnical Note

Modeling with Hysteresis Better Captures Grassland Growth in Asian Drylands

by Lijuan Miao, Yuyang Zhang, Evgenios Agathokleous, Gang Bao, Ziyu Zhu and Qiang Liu

Remote Sens. 2024, 16(11), 1838; https://doi.org/10.3390/rs16111838 - 22 May 2024

Viewed by 1196

Abstract

Climate warming hampers grassland growth, particularly in dryland regions. To preserve robust grassland growth and ensure the resilience of grassland in these arid areas, a comprehensive understanding of the interactions between vegetation and climate is imperative. However, existing studies often analyze climate–vegetation interactions [...] Read more.

Climate warming hampers grassland growth, particularly in dryland regions. To preserve robust grassland growth and ensure the resilience of grassland in these arid areas, a comprehensive understanding of the interactions between vegetation and climate is imperative. However, existing studies often analyze climate–vegetation interactions using concurrent vegetation indices and meteorological data, neglecting time-lagged influences from various determinants. To address this void, we employed the random forest machine learning method to predict the grassland NDVI (Normalized Difference Vegetation Index) in Asian drylands (including five central Asia countries, the Republic of Mongolia, and Parts of China) from 2001 to 2020, incorporating time-lag influences. We evaluated the prediction model’s performance using three indexes, namely the coefficient of determination (R²), root-mean-square error (RMSE), and Mean Absolute Error (MAE). The results underscore the superiority of the model incorporating time-lag influences, demonstrating its enhanced capability to capture the grassland NDVI in Asian drylands (R² ≥ 0.915, RMSE ≤ 0.033, MAE ≤ 0.019). Conversely, the model without time-lag influences exhibited relatively poor performance, notably inferior to the time-lag-inclusive model. The latter result aligns closely with remote sensing observations and more accurately reproduces the spatial distributions of the grassland NDVI in Asian drylands. Over the study period, the grassland NDVI in Asian drylands exhibited a weak decreasing trend, primarily concentrated in the western region. Notably, key factors influencing the grassland NDVI included the average grassland NDVI in the previous month, total precipitation in the current month, and average soil moisture in the previous month. This study not only pioneers a novel approach to predicting grassland growth but also contributes valuable insights for formulating sustainable strategies to preserve the integrity of grassland ecosystems. Full article

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

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31 pages, 9944 KiB

Open AccessArticle

Unveiling Deviations from IPCC Temperature Projections through Bayesian Downscaling and Assessment of CMIP6 General Circulation Models in a Climate-Vulnerable Region

by Giovanni-Breogán Ferreiro-Lera, Ángel Penas and Sara del Río

Remote Sens. 2024, 16(11), 1831; https://doi.org/10.3390/rs16111831 - 21 May 2024

Viewed by 1680

Abstract

The European Mediterranean Basin (Euro-Med), a region particularly vulnerable to global warming, notably lacks research aimed at assessing and enhancing the widely used remote climate detection products known as General Circulation Models (GCMs). In this study, the proficiency of GCMs in replicating reanalyzed [...] Read more.

The European Mediterranean Basin (Euro-Med), a region particularly vulnerable to global warming, notably lacks research aimed at assessing and enhancing the widely used remote climate detection products known as General Circulation Models (GCMs). In this study, the proficiency of GCMs in replicating reanalyzed 1981–2010 temperature data sourced from the ERA5 Land was assessed. Initially, the least data-modifying interpolation method for achieving a resolution match of 0.1° was ascertained. Subsequently, a pixel-by-pixel evaluation was conducted, employing five goodness-of-fit metrics. From these metrics, we compiled a Comprehensive Rating Index (CRI). A Multi-Model Ensemble using Random Forest was constructed and projected across three emission scenarios (SSP1-RCP2.6, SSP2-RCP4.5, and SSP5-RCP8.5) and timeframes (2026–2050, 2051–2075, and 2076–2100). Empirical Bayesian Kriging, selected for its minimal data alteration, supersedes the commonly employed Bilinear Interpolation. The evaluation results underscore MPI-ESM1-2-HR, GFDL-ESM4, CNRM-CM6-1, MRI-ESM2-0, CNRM-ESM2-1, and IPSL-CM6A-LR as top-performing models. Noteworthy geospatial disparities in model performance were observed. The projection outcomes, notably divergent from IPCC forecasts, revealed a warming trend of 1 to over 2 °C less than anticipated for spring and winter over the medium–long term, juxtaposed with heightened warming in mountainous/elevated regions. These findings could substantially refine temperature projections for the Euro-Med, facilitating the implementation of policy strategies to mitigate the effects of global warming in vulnerable regions worldwide. Full article

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

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17 pages, 8211 KiB

Open AccessArticle

The Influence of Spatial Heterogeneity of Urban Green Space on Surface Temperature

by Mengru Zhang, Jianguo Wang and Fei Zhang

Forests 2024, 15(5), 878; https://doi.org/10.3390/f15050878 - 17 May 2024

Cited by 4 | Viewed by 1523

Abstract

Urban green space (UGS) has been recognized as a key factor in enhancing the urban ecosystem balance, particularly in arid areas. It is often considered an effective means to mitigate the urban heat island (UHI) effect. In this study, the reference comparison method [...] Read more.

Urban green space (UGS) has been recognized as a key factor in enhancing the urban ecosystem balance, particularly in arid areas. It is often considered an effective means to mitigate the urban heat island (UHI) effect. In this study, the reference comparison method was utilized to optimize the process of nighttime lighting data; the random forest classification method was employed to extract UGS data; and the radiative transfer method was applied in land surface temperature (LST) inversion. Additionally, moving window analysis was conducted to assess the robustness of the results. The objective of this research was to analyze the spatial distribution characteristics of UGS and LST and to explore their bivariate local spatial autocorrelations by calculating four landscape metrics, including the aggregation index (AI), edge density (ED), patch density (PD), and area-weighted mean shape index (Shape_am). It was found that the distribution of UGS in the study area was uneven, with higher temperatures in the eastern and western regions and lower temperatures in the central and southern regions. The results also revealed that ED, PD, and Shape_am were negatively correlated with LST, with correlation coefficients being −0.469, −0.388, and −0.411, respectively, indicating that UGS in these regions were more effective in terms of cooling effect. Conversely, AI was found to be positively correlated with LST (Moran’ I index of 0.449), indicating that surface temperatures were relatively higher in regions of high aggregation. In essence, the fragmented, complex, and evenly distributed green patches in the study area provided a better cooling effect. These findings should persuade decision makers and municipal planners to allocate more UGS in cities for UHI alleviation to improve quality of life and enhance recreational opportunities. Full article

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

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21 pages, 4847 KiB

Open AccessArticle

Traces of Local Adaptive Acclimatization Response in the Tracheid Anatomical Traits between Dry and Wet Mesic Norway Spruce (Picea abies) Forests in Moravia, Czech Republic?

by Dimitrios Tsalagkas, Tomáš Novák, Marek Fajstavr, Hanuš Vavrčík, Vladimír Gryc, Petr Horáček and Kyriaki Giagli

Forests 2024, 15(5), 784; https://doi.org/10.3390/f15050784 - 29 Apr 2024

Cited by 1 | Viewed by 1146

Abstract

Norway spruce (Picea abies) forests in temperate zones are already reacting to short-term extreme summer heatwaves, threatening the vitality of trees and forest productivity, and can even lead to local and regional dieback events. Examining quantitative wood anatomy can provide helpful [...] Read more.

Norway spruce (Picea abies) forests in temperate zones are already reacting to short-term extreme summer heatwaves, threatening the vitality of trees and forest productivity, and can even lead to local and regional dieback events. Examining quantitative wood anatomy can provide helpful information in terms of understanding the physiology mechanisms and related responses of conifer trees to local environmental interactions in relation to tracheid adaptive capacity. This study analysed the tracheid functional anatomical traits (FATs) plasticity of six young Norway spruce trees growing in two mesic research plots with high annual precipitation (~43%) and air temperature differences during 2010–2017. The research plots are located in the sub-mountainous (Rájec Němčice) and mountainous (Bílý Kříž) belts of the Moravia region, Czech Republic. Vapour pressure deficit and cell wall reinforcement index (CWRI) were shown to be the most representative environmental parameters as proxies of dry conditions. Tracheid FATs indicated latewood phenological plasticity sensitivity, with more pronounced variability in the warmer and drier plots. Latewood tracheids of Norway spruce trees grown in the RAJ formed significantly thicker cell walls than BK during the studied period. The observed differences between the two research plots indicate additional support for tracheid cells’ hydraulic safety against cavitation and potential traces of adaptive acclimatization response. Full article

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

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24 pages, 3485 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

Viewed by 2690

Abstract

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)

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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 2333

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

Cited by 1 | Viewed by 1781

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

Cited by 2 | Viewed by 1383

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 1490

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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14 pages, 9137 KiB

Open AccessEditor’s ChoiceArticle

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

Cited by 6 | Viewed by 1904

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

Cited by 1 | Viewed by 1263

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

Cited by 6 | Viewed by 2901

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

Cited by 2 | Viewed by 2279

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

Cited by 4 | Viewed by 6225

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

Cited by 2 | Viewed by 2002

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

Cited by 2 | Viewed by 1653

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

Cited by 2 | Viewed by 1221

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 4 | Viewed by 1822

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

Cited by 1 | Viewed by 1216

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 - 8 Feb 2024

Cited by 16 | Viewed by 10793

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 - 7 Feb 2024

Cited by 2 | Viewed by 1838

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 - 2 Feb 2024

Cited by 2 | Viewed by 1771

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 10 | Viewed by 7215

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 - 8 Jan 2024

Cited by 5 | Viewed by 6095

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 - 5 Jan 2024

Cited by 1 | Viewed by 1802

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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