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Keywords = SSP5-8.5 emission scenario

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21 pages, 3111 KiB  
Article
Unraveling the Spatial Dynamics and Global Climate Change Response of Prominent Tropical Tree Species in Asia: Symplocos cochinchinensis and Beyond
by Haijun Li, Lihao Guo, Jingrui Zhang, Suile Li and Bo Liu
Forests 2025, 16(5), 715; https://doi.org/10.3390/f16050715 - 23 Apr 2025
Viewed by 228
Abstract
The tropical tree species Symplocos cochinchinensis plays a crucial role in ecological restoration and serves as a resource for traditional medicine, dyeing, and timber production. Assessing its distribution patterns and adaptive responses to global climate change is essential for maintaining ecosystems and developing [...] Read more.
The tropical tree species Symplocos cochinchinensis plays a crucial role in ecological restoration and serves as a resource for traditional medicine, dyeing, and timber production. Assessing its distribution patterns and adaptive responses to global climate change is essential for maintaining ecosystems and developing conservation strategies. This study elucidates the spatial distribution patterns and projects potential geographic shifts of the widely distributed tropical species S. cochinchinensis under climate change scenarios. A compilation of data from global and local herbaria and databases yielded 5050 occurrence records, covering the majority of its native range in the tropics and subtropics. We modeled the species’ potential habitats using the maximum entropy (MaxEnt) principle for current, 2050, and 2070 climate scenarios under high-emission SSP585. Our analysis reveals that sampling bias substantially influences the observed distribution patterns of S. cochinchinensis. Predictions indicate a decrease in barely suitable habitats and an increase in areas deemed highly suitable, suggesting climate change stress and an ecological niche shift towards areas with favorable microclimates with “Precipitation of Wettest Month” (Bio 13) and “Mean Temperature of Wettest Quarter” (Bio 8). Our findings reveal S. cochinchinensis’s adaptive resilience, offering valuable insights for developing strategies and conservation management in Southeast Asia, as well as a reference for the response of other common tropical species to climate change. Full article
(This article belongs to the Section Forest Meteorology and Climate Change)
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17 pages, 7997 KiB  
Article
Synergistic Effects of Multiple Monsoon Systems on Autumn Precipitation in West China
by Luchi Song, Lingli Fan, Chunqiao Lin, Jiahao Li and Jianjun Xu
Atmosphere 2025, 16(4), 481; https://doi.org/10.3390/atmos16040481 - 20 Apr 2025
Viewed by 120
Abstract
Multiple monsoon systems impact autumn precipitation in West China; however, their synergistic influence is unknown. Here, we employed statistical analysis of Global Precipitation Climatology Project Version 3.2 precipitation data, European Center for Medium-Range Weather Forecasts ERA5 reanalysis data, and Coupled Model Intercomparison Project [...] Read more.
Multiple monsoon systems impact autumn precipitation in West China; however, their synergistic influence is unknown. Here, we employed statistical analysis of Global Precipitation Climatology Project Version 3.2 precipitation data, European Center for Medium-Range Weather Forecasts ERA5 reanalysis data, and Coupled Model Intercomparison Project model data, and calculated four monsoon indices to analyze the features of the East Asian Monsoon, South Asian Monsoon, Asia Zonal Circulation, and Tibetan Plateau Monsoon, as well as their synergistic impacts on autumn precipitation in West China. The East Asian Monsoon negatively influences autumn precipitation in West China through closed high pressure over Northeast China. The South Asian Monsoon encloses West China between two areas of closed high pressure; strong high pressure to the north guides the abnormal transport of cold air in Northwest China, whereas strong western Pacific subtropical high pressure guides the transport of warm and wet air to West China, which is conducive to the formation of autumn precipitation in West China. During years of strong Asia Zonal Circulation, West China is controlled by an anomalous sinking airflow, which is not conducive to the occurrence of autumn rain. During strong Tibetan Plateau Monsoon, western and southwestern China are affected by plateau subsidence flow, resulting in less precipitation. Based on the CMIP6 model data, the study found that under the SSP5-8.5 emission scenario, the future trends of the four monsoon systems will show significant differences, and the amplitude of autumn and interannual precipitation oscillations in west China will increase. Full article
(This article belongs to the Section Climatology)
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24 pages, 5909 KiB  
Article
Spatiotemporal Dynamics and Future Projections of Carbon Use Efficiency on the Mongolian Plateau: A Remote Sensing and Machine Learning Approach
by Xinyu Yang, Qiang Yu, Buyanbaatar Avirmed, Yu Wang, Jikai Zhao, Weijie Sun, Huanjia Cui, Bowen Chi and Ji Long
Remote Sens. 2025, 17(8), 1392; https://doi.org/10.3390/rs17081392 - 14 Apr 2025
Viewed by 312
Abstract
The Mongolian Plateau, a critical area for global climate change response, faces increasing vulnerability from climate change and human activities impacting its arid ecosystems. This study integrates GeoDetector and machine learning to predict vegetation Carbon Use Efficiency (CUE) dynamics. It utilizes multi-source remote [...] Read more.
The Mongolian Plateau, a critical area for global climate change response, faces increasing vulnerability from climate change and human activities impacting its arid ecosystems. This study integrates GeoDetector and machine learning to predict vegetation Carbon Use Efficiency (CUE) dynamics. It utilizes multi-source remote sensing data (MODIS, ERA5-Land) from 2000 to 2020 and incorporates four Shared Socioeconomic Pathways (SSPs) from CMIP6. The results indicate the following: (1) significant spatial variation exists, with high-value CUE areas (≥0.7) in the northwest due to favorable climatic conditions, while low-value areas (<0.6) in the east are affected by decreasing precipitation and overgrazing; (2) CUE increased at an annual rate of 1.03%, with a 43% acceleration after the 2005 climate shift, highlighting the synergistic effects of ecological engineering; (3) our findings reveal that the interaction of evapotranspiration and temperature dominates CUE spatial differentiation, with the random forest model accurately predicting CUE dynamics (root mean square error (RMSE) = 0.0819); (4) scenario simulations show the SSP3-7.0 pathway will peak CUE at 0.6103 by 2050, while the SSP5-8.5 scenario will significantly reduce spatial heterogeneity. The study recommends enhancing water–heat regulation in the northwest and implementing vegetation restoration strategies in the east, alongside establishing a CUE warning system. This research offers valuable insights for improving carbon sequestration and climate resilience in arid ecosystems, with significant implications for carbon management under high-emission scenarios. Full article
(This article belongs to the Section Biogeosciences Remote Sensing)
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16 pages, 5810 KiB  
Article
Deep Learning Downscaling of Precipitation Projection over Central Asia
by Yichang Jiang, Jianing Guo, Lei Fan, Hui Sun and Xiaoning Xie
Water 2025, 17(7), 1089; https://doi.org/10.3390/w17071089 - 5 Apr 2025
Viewed by 250
Abstract
Central Asia, as a chronically water-stressed region marked by extreme aridity, faces significant environmental challenges from intensifying desertification and deteriorating ecological stability. The region’s vulnerability to shifting precipitation regimes and extreme hydrometeorological events has been magnified under anthropogenic climate forcing. Although global climate [...] Read more.
Central Asia, as a chronically water-stressed region marked by extreme aridity, faces significant environmental challenges from intensifying desertification and deteriorating ecological stability. The region’s vulnerability to shifting precipitation regimes and extreme hydrometeorological events has been magnified under anthropogenic climate forcing. Although global climate models (GCMs) remain essential tools for climate projections, their utility in Central Asia’s complex terrain is constrained by inherent limitations: coarse spatial resolution (~100–250 km) and imperfect parameterization of orographic precipitation mechanisms. This investigation advances precipitation modeling through deep learning-enhanced statistical downscaling, employing convolutional neural networks (CNNs) to generate high-resolution precipitation data at approximately 10 km resolution. Our results show that the deep learning models successfully simulate the high center of precipitation and extreme precipitation near the Tianshan Mountains, exhibiting high spatial applicability. Under intermediate (SSP-245) and high-emission (SSP-585) future scenarios, the increase in extreme precipitation over the next century is significantly more pronounced compared to mean precipitation. By the end of the 21st century, the interannual variability of mean precipitation and extreme precipitation will become even larger under SSP-585, indicating an increased risk of extreme droughts/floods in Central Asia under high greenhouse gas emissions. Our findings provide technical support for climate change impact assessments in the region and highlight the potential of CNN-based downscaling for future climate change studies. Full article
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19 pages, 8881 KiB  
Article
Global Warming Drives Shifts in the Suitable Habitats of Subalpine Shrublands in the Hengduan Mountains Region in China
by Huayong Zhang, Yunyan Yu, Xiande Ji, Zhongyu Wang and Zhao Liu
Forests 2025, 16(4), 624; https://doi.org/10.3390/f16040624 - 2 Apr 2025
Viewed by 256
Abstract
Subalpine shrubland is an important vegetation type in the Hengduan Mountains region of China, and its distribution has been substantially influenced by global warming. In this research, four subalpine shrub communities in the Hengduan Mountains were selected: Rhododendron heliolepis Franch. scrub, Rhododendron flavidum [...] Read more.
Subalpine shrubland is an important vegetation type in the Hengduan Mountains region of China, and its distribution has been substantially influenced by global warming. In this research, four subalpine shrub communities in the Hengduan Mountains were selected: Rhododendron heliolepis Franch. scrub, Rhododendron flavidum Franch. scrub, Quercus monimotricha (Hand.-Mazz.) Hand.-Mazz. scrub, and Pinus yunnanensis var. pygmaea (Hsueh ex C. Y. Cheng, W. C. Cheng & L. K. Fu) Hsueh scrub. A MaxEnt model was used to assess the suitable habitats and their primary drivers of four subalpine shrublands in China under different climate scenarios. Our results indicate the following: (1) The suitable habitat areas of the four subalpine shrublands exhibit a predominant distribution within the Hengduan Mountains region, with small populations in the Himalayas and Wumeng Mountain. Temperature and precipitation are identified as the primary drivers influencing the suitable habitat areas of the four subalpine shrublands, and the temperature factor is more influential than the precipitation factor. Furthermore, the contribution rate of slope to Quercus monimotricha scrub is 19.2%, which cannot be disregarded. (2) Under future climate scenarios, the total suitable habitats of the four subalpine shrublands show an expanding trend. However, the highly suitable areas of three shrublands (Rhododendron flavidum scrub, Quercus monimotricha scrub, and Pinus yunnanensis var. pygmaea scrub) show a contracting trend under the high-carbon-emission scenario (SSP585). (3) Driven by global warming, the suitable habitat areas of Rhododendron heliolepis scrub, Rhododendron flavidum scrub, and Pinus yunnanensis var. pygmaea scrub shift toward higher elevations in the northwest, while the distribution of Quercus monimotricha scrub varies under different carbon emission scenarios, with a much smaller shift range than the other three scrubs. Our study contributes valuable insights into the spatiotemporal dynamics of subalpine shrublands in China under climate change, providing scientific guidance for biodiversity conservation and ecosystem restoration. Full article
(This article belongs to the Section Forest Meteorology and Climate Change)
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24 pages, 6891 KiB  
Article
Assessment of Future Rainfall Quantile Changes in South Korea Based on a CMIP6 Multi-Model Ensemble
by Sunghun Kim, Ju-Young Shin and Jun-Haeng Heo
Water 2025, 17(6), 894; https://doi.org/10.3390/w17060894 - 20 Mar 2025
Viewed by 452
Abstract
Climate change presents considerable challenges to hydrological stability by modifying precipitation patterns and exacerbating the frequency and intensity of extreme rainfall events. This research evaluates the prospective alterations in rainfall quantiles in South Korea by employing a multi-model ensemble (MME) derived from 23 [...] Read more.
Climate change presents considerable challenges to hydrological stability by modifying precipitation patterns and exacerbating the frequency and intensity of extreme rainfall events. This research evaluates the prospective alterations in rainfall quantiles in South Korea by employing a multi-model ensemble (MME) derived from 23 Global Climate Models (GCMs) associated with the Coupled Model Intercomparison Project Phase 6 (CMIP6) under four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). Historical rainfall data from simulations (1985–2014) and future projections (2015–2044, 2043–2072, and 2071–2100) were analyzed across a total of 615 sites. Statistical Quantile Mapping (SQM) bias correction significantly enhanced the accuracy of projections (RMSE reduction of 63.0–85.3%, Pbias reduction of 93.6%, and R2 increase of 0.73). An uncertainty analysis revealed model uncertainty to be the dominant factor (approximately 71.87–70.49%) in the near- to mid-term periods, and scenario uncertainty increased notably (up to 5.94%) by the end of the century. The results indicate substantial temporal and spatial changes, notably including increased precipitation in central inland and eastern coastal regions, with peak monthly increases exceeding 40 mm under high-emission scenarios. Under the SSP2-4.5 and SSP5-8.5 scenarios, the 100-year rainfall quantile is projected to increase by over 40% across significant portions of the country, emphasizing growing challenges for water resource management and infrastructure planning. These findings provide critical insights for water resource management, disaster mitigation, and climate adaptation strategies in South Korea. Full article
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21 pages, 13744 KiB  
Article
Spatiotemporal Characteristics, Causes, and Prediction of Wildfires in North China: A Study Using Satellite, Reanalysis, and Climate Model Datasets
by Mengxin Bai, Peng Zhang, Pei Xing, Wupeng Du, Zhixin Hao, Hui Zhang, Yifan Shi and Lulu Liu
Remote Sens. 2025, 17(6), 1038; https://doi.org/10.3390/rs17061038 - 15 Mar 2025
Viewed by 647
Abstract
Understanding the characteristics of wildfires in North China is critical for advancing regional fire danger prediction and management strategies. This study employed satellite-based burned area products of the Global Fire Emissions Database (GFED) and reanalysis of climate datasets to investigate the spatiotemporal characteristics [...] Read more.
Understanding the characteristics of wildfires in North China is critical for advancing regional fire danger prediction and management strategies. This study employed satellite-based burned area products of the Global Fire Emissions Database (GFED) and reanalysis of climate datasets to investigate the spatiotemporal characteristics of wildfires, as well as their relationships with fire danger indices and climatic drivers. The results revealed distinct seasonal variability, with the maximum burned area extent and intensity occurring during the March–April period. Notably, the fine fuel moisture code (FFMC) demonstrated a stronger correlation with burned areas compared to other fire danger or climate indices, both in temporal series and spatial patterns. Further analysis through the self-organizing map (SOM) clustering of FFMC composites then revealed six distinct modes, with the SOM1 mode closely matching the spatial distribution of burned areas in North China. A trend analysis indicated a 7.75% 10a−1 (p < 0.05) increase in SOM1 occurrence frequency, associated with persistent high-pressure systems that suppress convective activity through (1) inhibited meridional water vapor transport and (2) reduced cloud condensation nuclei formation. These synoptic conditions created favorable conditions for the occurrence of wildfires. Finally, we developed a prediction model for burned areas, leveraging the strong correlation between the FFMC and burned areas. Both the SSP245 and SSP585 scenarios suggest an accelerated, increasing trend of burned areas in the future. These findings emphasize the importance of understanding the spatiotemporal characteristics and underlying causes of wildfires, providing critical insights for developing adaptive wildfire management frameworks in North China. Full article
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19 pages, 6876 KiB  
Article
Global Climate Convergence from 1980 to 2022 Led to Significant Increase in Vegetation Productivity
by Hongjuan Zhu and Chuanhua Li
Land 2025, 14(3), 570; https://doi.org/10.3390/land14030570 - 8 Mar 2025
Viewed by 406
Abstract
Changes in global temperature and precipitation over the past few decades have caused significant alterations in global climate patterns. However, the impact of these changes on global vegetation productivity remains unclear. This article evaluates the effect of converging climate patterns on global vegetation [...] Read more.
Changes in global temperature and precipitation over the past few decades have caused significant alterations in global climate patterns. However, the impact of these changes on global vegetation productivity remains unclear. This article evaluates the effect of converging climate patterns on global vegetation productivity, focusing on the land outside Antarctica as the study area, and theoretically substantiates the validity of the findings. The study reveals the climate status of the historical period of 1980–2022 and the SSP126 scenario, where convergence in precipitation patterns leads to a significant increase in global NPP, while the convergence of temperature patterns has a much smaller impact on NPP than precipitation. Under the high-emission scenarios SSP245 and SSP585, the laws are reversed: converging temperature patterns lead to a decrease in NPP, while converging precipitation patterns have an insignificant impact on NPP. Climate change under these three scenarios indicates the detrimental effects of climate patterns under high emissions on vegetation productivity. This study fills a gap in the literature on the impact of climate patterns on vegetation productivity. Full article
(This article belongs to the Section Land–Climate Interactions)
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17 pages, 14185 KiB  
Article
Impacts of Climate Change on the Potential Suitable Ecological Niches of the Endemic and Endangered Conifer Pinus bungeana in China
by Xiaowei Zhang, Yuke Fan, Furong Niu, Songsong Lu, Weibo Du, Xuhu Wang and Xiaolei Zhou
Forests 2025, 16(3), 462; https://doi.org/10.3390/f16030462 - 5 Mar 2025
Cited by 1 | Viewed by 476
Abstract
As climate change continues to alter species distributions, Pinus bungeana, an endangered conifer of significant ecological and ornamental value, faces heightened vulnerability, underscoring the critical need to understand and predict its future habitat shifts. Here, we used 83 effective geographic distribution records, [...] Read more.
As climate change continues to alter species distributions, Pinus bungeana, an endangered conifer of significant ecological and ornamental value, faces heightened vulnerability, underscoring the critical need to understand and predict its future habitat shifts. Here, we used 83 effective geographic distribution records, along with climate, topography, soil, and drought indices, to simulate the potential distribution of suitable ecological niches for P. bungeana under current conditions and across three future time periods (2040–2060, 2060–2080, and 2080–2100) under two shared socioeconomic pathways: SSP126 (low emissions) and SSP585 (high emissions), using the maximum entropy (MaxEnt) model. The results show that the area under the receiver operating characteristic curve (AUC) for all simulations exceeded 0.973, indicating high predictive accuracy. Soil moisture, the minimum temperature of the coldest month, temperature seasonality, isothermality, the precipitation of the wettest quarter, and altitude were identified as key environmental factors limiting the distribution of P. bungeana, with soil moisture and the minimum temperature of the coldest month being the most important factors. Under the current climatic conditions, the potentially suitable ecological niches for P. bungeana were primarily located in Shaanxi Province, southern Shanxi Province, southeastern Gansu Province, northeastern Sichuan Province, Henan Province, and northwestern Hubei Province, covering approximately 75.59 × 104 km2. However, under the future climate scenarios, highly suitable areas were projected to contract, with the rate of decline varying significantly between scenarios. Despite this, the total area of potentially suitable ecological niches was predicted to expand in the future periods. Additionally, a pronounced eastward shift in P. bungeana’s distribution was projected, especially under the high-emission SSP585 scenario. These findings provide insights into the potential impacts of climate change on the distribution of P. bungeana, and they offer valuable guidance for its conservation strategies and habitat management in the context of climate change. Full article
(This article belongs to the Section Forest Meteorology and Climate Change)
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14 pages, 4797 KiB  
Article
MaxEnt-Based Distribution Modeling of the Invasive Species Phragmites australis Under Climate Change Conditions in Iraq
by Nabaz R. Khwarahm
Plants 2025, 14(5), 768; https://doi.org/10.3390/plants14050768 - 2 Mar 2025
Viewed by 1252
Abstract
Phragmites australis (common reed), a recently introduced invasive species in Iraq, has swiftly established itself as a vigorous perennial plant, significantly impacting the biodiversity and ecosystem functions of Iraqi ecoregions with alarming consequences. There is an insufficient understanding of both the current distribution [...] Read more.
Phragmites australis (common reed), a recently introduced invasive species in Iraq, has swiftly established itself as a vigorous perennial plant, significantly impacting the biodiversity and ecosystem functions of Iraqi ecoregions with alarming consequences. There is an insufficient understanding of both the current distribution and possible future trends under climate change scenarios. Consequently, this study seeks to model the current and future potential distribution of this invasive species in Iraq using machine learning techniques (i.e., MaxEnt) alongside geospatial tools integrated within a GIS framework. Land-cover features, such as herbaceous zones, wetlands, annual precipitation, and elevation, emerged as optimal conditioning factors for supporting the species’ invasiveness and habitat through vegetation cover and moisture retention. These factors collectively contributed by nearly 85% to the distribution of P. australis in Iraq. In addition, the results indicate a net decline in high-suitability habitats for P. australis under both the SSP126 (moderate mitigation; 5.33% habitat loss) and SSP585 (high emissions; 6.74% habitat loss) scenarios, with losses concentrated in southern and northern Iraq. The model demonstrated robust reliability, achieving an AUC score of 0.9 ± 0.012, which reflects high predictive accuracy. The study area covers approximately 430,632.17 km2, of which 64,065.66 km2 (14.87% of the total region) was classified as the optimal habitat for P. australis. While climate projections indicate an overall decline (i.e., SSP126 (5.33% loss) and SSP585 (6.74% loss)) in suitable habitats for P. australis across Iraq, certain localized regions may experience increased habitat suitability, reflecting potential gains (i.e., SSP126 (3.58% gain) and SSP585 (1.82% gain)) in specific areas. Policymakers should focus on regions with emerging suitability risks for proactive monitoring and management. Additionally, areas already infested by the species require enhanced surveillance and containment measures to mitigate ecological and socioeconomic impacts. Full article
(This article belongs to the Section Plant Response to Abiotic Stress and Climate Change)
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28 pages, 29712 KiB  
Article
Multi-Temporal Relative Sea Level Rise Scenarios up to 2150 for the Venice Lagoon (Italy)
by Marco Anzidei, Cristiano Tolomei, Daniele Trippanera, Tommaso Alberti, Alessandro Bosman, Carlo Alberto Brunori, Enrico Serpelloni, Antonio Vecchio, Antonio Falciano and Giuliana Deli
Remote Sens. 2025, 17(5), 820; https://doi.org/10.3390/rs17050820 - 26 Feb 2025
Cited by 1 | Viewed by 2262
Abstract
The historical City of Venice, with its lagoon, has been severely exposed to repeated marine flooding since historical times due to the combined effects of sea level rise (SLR) and land subsidence (LS) by natural and anthropogenic causes. Although the sea level change [...] Read more.
The historical City of Venice, with its lagoon, has been severely exposed to repeated marine flooding since historical times due to the combined effects of sea level rise (SLR) and land subsidence (LS) by natural and anthropogenic causes. Although the sea level change in this area has been studied for several years, no detailed flooding scenarios have yet been realized to predict the effects of the expected SLR in the coming decades on the coasts and islands of the lagoon due to global warming. From the analysis of geodetic data and climatic projections for the Shared Socioeconomic Pathways (SSP1-2.6; SSP3-7.0 and SSP5-8.5) released in the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC), we estimated the rates of LS, the projected local relative sea level rise (RSLR), and the expected extent of flooded surfaces for 11 selected areas of the Venice Lagoon for the years 2050, 2100, and 2150 AD. Vertical Land Movements (VLM) were obtained from the integrated analysis of Global Navigation Satellite System (GNSS) and Interferometry Synthetic Aperture Radar (InSAR) data in the time spans of 1996–2023 and 2017–2023, respectively. The spatial distribution of VLM at 1–3 mm/yr, with maximum values up to 7 mm/yr, is driving the observed variable trend in the RSLR across the lagoon, as also shown by the analysis of the tide gauge data. This is leading to different expected flooding scenarios in the emerging sectors of the investigated area. Scenarios were projected on accurate high-resolution Digital Surface Models (DSMs) derived from LiDAR data. By 2150, over 112 km2 is at risk of flooding for the SSP1-2.6 low-emission scenario, with critical values of 139 km2 for the SSP5-8.5 high-emission scenario. In the case of extreme events of high water levels caused by the joint effects of astronomical tides, seiches, and atmospheric forcing, the RSLR in 2150 may temporarily increase up to 3.47 m above the reference level of the Punta della Salute tide gauge station. This results in up to 65% of land flooding. This extreme scenario poses the question of the future durability and effectiveness of the MoSE (Modulo Sperimentale Elettromeccanico), an artificial barrier that protects the lagoon from high tides, SLR, flooding, and storm surges up to 3 m, which could be submerged by the sea around 2100 AD as a consequence of global warming. Finally, the expected scenarios highlight the need for the local communities to improve the flood resiliency plans to mitigate the consequences of the expected RSLR by 2150 in the UNESCO site of Venice and the unique environmental area of its lagoon. Full article
(This article belongs to the Section Environmental Remote Sensing)
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17 pages, 6963 KiB  
Article
Projected Drought Intensification in the Büyük Menderes Basin Under CMIP6 Climate Scenarios
by Farzad Rotbeei, Mustafa Nuri Balov, Mir Jafar Sadegh Safari and Babak Vaheddoost
Climate 2025, 13(3), 47; https://doi.org/10.3390/cli13030047 - 26 Feb 2025
Viewed by 418
Abstract
The amplitude and interval of drought events are expected to enhance in upcoming years resulting from global warming and climate alterations. Understanding future drought events’ potential impacts is important for effective regional adaptation and mitigation approaches. The main goal of this research is [...] Read more.
The amplitude and interval of drought events are expected to enhance in upcoming years resulting from global warming and climate alterations. Understanding future drought events’ potential impacts is important for effective regional adaptation and mitigation approaches. The main goal of this research is to study the impacts of climate change on drought in the Büyük Menderes Basin located in the Aegean region of western Türkiye by using the outcomes of three general circulation models (GCMs) from CMIP6 considering two different emission scenarios (SSP2-4.5 and SSP5-8.5). Following a bias correction using a linear scaling method, daily precipitation and temperature projections are used to compute the Standardized Precipitation Evapotranspiration Index (SPEI). The effectiveness of the GCMs in projecting precipitation and temperature is evaluated using observational data from the reference period (1985–2014). Future drought conditions are then assessed based on drought indices for three periods: 2015–2040 (near future), 2041–2070 (mid-term future), and 2071–2100 (late future). Consequently, the number of dry months is projected and expected to elevate, informed by SSP2-4.5 and SSP5-8.5 scenarios, during the late-century timeframe (2071–2100) in comparison to the baseline period (1985–2014). The findings of this study offer an important understanding for crafting adaptation strategies aimed at reducing future drought impacts in the Büyük Menderes Basin in the face of changing climate conditions. Full article
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14 pages, 3110 KiB  
Article
Sugarcane Distribution Simulation and Climate Change Impact Analysis in China
by Zhiluo Zhou, Xiaohuang Liu, Run Liu, Jiufen Liu, Wenjie Liu, Qiu Yang, Xinping Luo, Ran Wang, Liyuan Xing, Honghui Zhao and Chao Wang
Agriculture 2025, 15(5), 491; https://doi.org/10.3390/agriculture15050491 - 25 Feb 2025
Viewed by 413
Abstract
Sugarcane is an important economic crop in China, and its yield is significantly affected by climate change. With climate change leading to significant shifts in environmental conditions, the suitable cultivation zones for the crop are expected to change, impacting China’s sugarcane production and [...] Read more.
Sugarcane is an important economic crop in China, and its yield is significantly affected by climate change. With climate change leading to significant shifts in environmental conditions, the suitable cultivation zones for the crop are expected to change, impacting China’s sugarcane production and industry layout. This study aims to analyze potential distribution areas for sugarcane under different climate change scenarios, providing scientific guidance for optimizing future cultivation zones and resource allocation. Data on sugarcane distribution in China and 38 related environmental factors were collected. After excluding variables with high correlations, the MaxEnt model and ArcGIS 10.2 software were used to analyze the main environmental factors affecting crop survival based on contribution rates and the Jackknife method. The study simulated the suitable areas in China during the historical period and predicted future suitable areas under three greenhouse gas emission scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). The results showed that the Area Under the Receiver Operating Characteristic Curve (AUC) was 0.921, indicating high accuracy in the model’s analysis of suitability zones. The three dominant environmental variables influencing sugarcane distribution in China were identified as annual precipitation, min temperature of the coldest month and elevation. The primary suitable zones are concentrated in southern China, forming a “V” shape, including regions such as Guangxi, Sichuan, Guizhou, Yunnan, Hainan, and Fujian. In the future, the area of unsuitable zones is expected to decrease. The overall suitable zones for sugarcane are projected to shift towards the central and northern parts of China. This research can assist China’s sugarcane industry in addressing the challenges of climate change and provide references for its cultivation, industry layout optimization, and the selection of new planting sites. Full article
(This article belongs to the Section Ecosystem, Environment and Climate Change in Agriculture)
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28 pages, 22483 KiB  
Article
Prediction of Land Use Change and Carbon Storage in Lijiang River Basin Based on InVEST-PLUS Model and SSP-RCP Scenario
by Jing Jing, Feili Wei, Hong Jiang, Zhantu Chen, Shuang Lv, Tengfang Li, Weiwei Li and Yi Tang
Land 2025, 14(3), 460; https://doi.org/10.3390/land14030460 - 23 Feb 2025
Viewed by 610
Abstract
Global climate change and changes in land use structures during rapid urbanization have profoundly impacted ecosystem carbon storage. Previous studies have not combined different climate scenarios and land use patterns to predict carbon storage. Using scenarios from both the InVEST-PLUS model and SSP-RCP, [...] Read more.
Global climate change and changes in land use structures during rapid urbanization have profoundly impacted ecosystem carbon storage. Previous studies have not combined different climate scenarios and land use patterns to predict carbon storage. Using scenarios from both the InVEST-PLUS model and SSP-RCP, combined with multi-source remote sensing data, this study takes the Lijiang River Basin as the study area to explore the dynamic changes in land use and carbon storage under different climate scenarios. The findings are as follows: (1) From 2000 to 2020, cultivated and construction land increased, while forest land significantly decreased, lowering from 4331.404 km2 to 4111.936 km2. This land use change mainly manifests in the significant transformation of forest land into cultivated and construction lands. Under different climate scenarios, the cultivated and construction lands will continue to expand, the forest land will decrease, and the grassland area will increase. (2) Total carbon storage decreased significantly from 2000 to 2020, with forest carbon storage changing the most significantly, for a total reduction of 5,540,612.13 tons, followed by grassland and water area. Regardless of the future scenario, the total carbon storage in the Lijiang River Basin will experience a decreasing trend; the decline in carbon reserves is most significant in the SSP585 scenario and smallest in the SSP126 scenario, with slight increases even appearing in some regions. (3) From the perspective of land use change, the large-scale expansion of construction land in the process of rapid urbanization has occupied a large amount of ecological land, such as forests and grasslands, and this is the main reason for the reduction in total carbon storage in the basin. From the perspective of climate change scenarios, a global temperature increase caused by a high-emission scenario (SSP585) may exceed the optimal growth temperature for some plants, inhibit the carbon absorption capacity of vegetation, and thus reduce the carbon fixation capacity of forest land and grassland. Therefore, to maintain long-term climate goals and sustainable development, the SSP126 scenario should be prioritized to strengthen the protection of forest resources in the northern and central regions of the Lijiang River Basin, balance the relationship between ecological protection and urbanization, avoid the occupation of ecological land by excessive urbanization, and improve the carbon sink potential of the basin. These research results can provide a scientific basis for the optimization of land spatial patterns, ecological restoration and protection, and the enhancement of carbon sink potential in the Lijiang River Basin under the “double carbon” goal. Full article
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18 pages, 8681 KiB  
Article
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
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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
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