We examine possible funding sources for constructing Climate Change Haven Communities on a global basis. Areas of the planet that have the potential to house persons migrating to “safe havens” in their own or other ...We examine possible funding sources for constructing Climate Change Haven Communities on a global basis. Areas of the planet that have the potential to house persons migrating to “safe havens” in their own or other countries will require the rapid construction of communities capable of supporting them, their families, businesses and farms. However, different political-economic conditions are found across the areas which can serve as locations for these Climate Change Haven Communities. We develop funding and construction strategies for the United States (free-market capitalism), France and Spain (European Union supported economies), and Taiwan region (state-directed economy). The proposals for the Taiwan region should also be applicable to the rest of China.展开更多
BACKGROUND Lumbar interbody fusion(LIF)is the primary treatment for lumbar degenerative diseases.Elderly patients are prone to anxiety and depression after undergoing surgery,which affects their postoperative recovery...BACKGROUND Lumbar interbody fusion(LIF)is the primary treatment for lumbar degenerative diseases.Elderly patients are prone to anxiety and depression after undergoing surgery,which affects their postoperative recovery speed and quality of life.Effective prevention of anxiety and depression in elderly patients has become an urgent problem.AIM To investigate the trajectory of anxiety and depression levels in elderly patients after LIF,and the influencing factors.METHODS Random sampling was used to select 239 elderly patients who underwent LIF from January 2020 to December 2024 in Shenzhen Pingle Orthopedic Hospital.General information and surgery-related indices were recorded,and participants completed measures of psychological status,lumbar spine dysfunction,and quality of life.A latent class growth model was used to analyze the post-LIF trajectory of anxiety and depression levels,and unordered multi-categorical logistic regression was used to analyze the influencing factors.RESULTS Three trajectories of change in anxiety level were identified:Increasing anxiety(n=26,10.88%),decreasing anxiety(n=27,11.30%),and stable anxiety(n=186,77.82%).Likewise,three trajectories of change in depression level were identified:Increasing depression(n=30,12.55%),decreasing depression(n=26,10.88%),and stable depression(n=183,76.57%).Regression analysis showed that having no partner,female sex,elevated Oswestry dysfunction index(ODI)scores,and reduced 36-Item Short Form Health Survey scores all contributed to increased anxiety levels,whereas female sex,postoperative opioid use,and elevated ODI scores all contributed to increased depression levels.CONCLUSION During clinical observation,combining factors to predict anxiety and depression in post-LIF elderly patients enables timely intervention,quickens recovery,and enhances quality of life.展开更多
Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectra...Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectral similarity between buildings and backgrounds,sensor variations,and insufficient computational efficiency.To address these challenges,this paper proposes a novel Multi-scale Efficient Wavelet-based Change Detection Network(MewCDNet),which integrates the advantages of Convolutional Neural Networks and Transformers,balances computational costs,and achieves high-performance building change detection.The network employs EfficientNet-B4 as the backbone for hierarchical feature extraction,integrates multi-level feature maps through a multi-scale fusion strategy,and incorporates two key modules:Cross-temporal Difference Detection(CTDD)and Cross-scale Wavelet Refinement(CSWR).CTDD adopts a dual-branch architecture that combines pixel-wise differencing with semanticaware Euclidean distance weighting to enhance the distinction between true changes and background noise.CSWR integrates Haar-based Discrete Wavelet Transform with multi-head cross-attention mechanisms,enabling cross-scale feature fusion while significantly improving edge localization and suppressing spurious changes.Extensive experiments on four benchmark datasets demonstrate MewCDNet’s superiority over comparison methods:achieving F1 scores of 91.54%on LEVIR,93.70%on WHUCD,and 64.96%on S2Looking for building change detection.Furthermore,MewCDNet exhibits optimal performance on the multi-class⋅SYSU dataset(F1:82.71%),highlighting its exceptional generalization capability.展开更多
This study investigates climate-and human-induced hydrological changes in the Zavkhan River-Khyargas Lake Basin,a highly sensitive arid and semi-arid region of Central Asia.Using Mann-Kendall,innovative trend analysis...This study investigates climate-and human-induced hydrological changes in the Zavkhan River-Khyargas Lake Basin,a highly sensitive arid and semi-arid region of Central Asia.Using Mann-Kendall,innovative trend analysis,and Sen's slope estimation methods,historical climate trends(1980-2100)were analyzed,while land cover changes represented human impacts.Future projections were simulated using the MIROC model with Shared Socioeconomic Pathways(SSPs)and the Tank model.Results show that during the past 40 years,air temperature significantly increased(Z=3.93^(***)),while precipitation(Z=-1.54^(*))and river flow(Z=-1.73^(*))both declined.The Khyargas Lake water level dropped markedly(Z=-5.57***).Land cover analysis reveals expanded cropland and impervious areas due to human activity.Under the SSP1.26 scenario,which assumes minimal climate change,air temperature is projected to rise by 2.0℃,precipitation by 21.8 mm,and river discharge by 1.61 m^(3)/s between 2000 and 2100.These findings indicate that both global warming and intensified land use have substantially altered hydrological and climatic processes in the basin,highlighting the vulnerability of western Mongolia's water resources to combined climatic and anthropogenic influence.展开更多
Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diver...Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diverse sensitivities of surface fluxes.This study utilizes data from the Flux-Anomaly-Forced Model Intercomparison Project to investigate how ocean salinity responds to perturbations of surface fluxes.The findings indicate the emergence of a sea surface salinity(SSS)dipole pattern predominantly in the North Atlantic and Pacific fresh pools,driven by surface flux perturbations.This results in an intensification of the“salty gets saltier and fresh gets fresher”SSS pattern across the global ocean.The spatial pattern amplification(PA)of SSS under global warming is estimated to be approximately 11.5%,with surface water flux perturbations being the most significant contributor to salinity PA,accounting for 8.1% of the change after 70 years in experiments since pre-industrial control(piControl).Notably,the zonal-depth distribution of salinity in the upper ocean exhibits lighter seawater above the denser water,with bowed isopycnals in the upper 400 m.This stable stratification inhibits vertical mixing of salinity and temperature.In response to the flux perturbations,there is a strong positive feedback due to consequent freshening.It is hypothesized that under global warming,an SSS amplification of 7.2%/℃ and a mixed-layer depth amplification of 12.5%/℃ will occur in the global ocean.It suggests that the salinity effect can exert a more stable ocean to hinder the downward transfer of heat,which provides positive feedback to future global warming.展开更多
To address climate change and highlight its global nature,the United Nations Framework Convention on Climate Change(UNFCCC)was adopted for the first time in history within the UN framework on May 9,1992,clearly establ...To address climate change and highlight its global nature,the United Nations Framework Convention on Climate Change(UNFCCC)was adopted for the first time in history within the UN framework on May 9,1992,clearly establishing the obligations of developed countries to take the lead in emission reduction and provide financial,technological,and capacity-building support to developing countries.Particularly since the 2015 Paris Agreement,successive UN climate conferences have placed high emphasis on financial and technological matters,with financial arrangements demonstrating an increasingly specific trend in recent years.The Glasgow Climate Pact adopted in 2021 urges developed country Parties to deliver on their commitment to the goal of providing USD 100 billion to developing country prties,while also urging developed country parties to at least double their provision of climate finance to developing country parties by 2025 compared to 2019 levels.展开更多
Low-carbon urban development in China can pave the way to achieve the dualcarbon goal.Exploring how land use changes(LUCs)impact carbon storage(CS)under multi-climate scenarios in different urban agglomerations helps ...Low-carbon urban development in China can pave the way to achieve the dualcarbon goal.Exploring how land use changes(LUCs)impact carbon storage(CS)under multi-climate scenarios in different urban agglomerations helps to formulate differential scientific carbon mitigation policies.In this regard,this study constructs an integrated model of SD-PLUS-InVEST to simulate LUCs and CS changes under multi-climate change-based scenarios(SSP126,SSP245,SSP585)for three major urban agglomerations(3UAs)in the Yangtze River Economic Belt.Results demonstrate that land use demand in the 3UAs changes considerably in each scenario.Construction land in the 3UAs remains the most important growth category for the coming decade,but its increase varies in different scenarios.CS in the Yangtze River Delta Urban Agglomeration(YRDUA)and Mid-Yangtze River Urban Agglomeration(MYRUA)shows a similar downward trend under different scenarios,with scenario SSP245 decreasing the most,to 184,713.526 Tg and 384,459.729 Tg,respectively.CS in the Cheng-Yu(Chengdu-Chongqing)Urban Agglomeration(CYUA)exhibits the opposite upward trend,with scenario SSP126 increasing the most to 153,007.973 Tg.The major cause of CS loss remains the conversion of forest land to construction land in the YRDUA and MYRUA under different scenarios.However,in the CYUA,the conversion of forest land to cultivated land is the major driver of CS loss under scenario SSP126.In contrast,the conversion of cultivated land to construction land dominantly drives CS loss under scenarios SSP245 and SSP585.The conversion of water body to other land use types is the major cause of CS gain in the YRDUA and MYRUA under different scenarios.At the same time,in the CYUA,the driver is the conversion of cultivated land to forest land.These findings demonstrate the significance of the low-carbon development in urban agglomerations at different development stages at home and abroad.展开更多
Climate warming and humidification trends have significantly influenced vegetation growth patterns in Chinese semi-arid areas.Exploring vegetation dynamics is crucial for understanding regional ecosystem structure and...Climate warming and humidification trends have significantly influenced vegetation growth patterns in Chinese semi-arid areas.Exploring vegetation dynamics is crucial for understanding regional ecosystem structure and improving the efforts of ecosystem restoration.However,the applicability of various vegetation indices(VIs)in these arid areas remains uncertain.Evaluating the applicability of multiple VIs for vegetation monitoring can elucidate the variability of VIs performance at regional scale.Therefore,this study selected the Zuli River Basin(ZLRB),a typical loess hilly watershed in the semi-arid areas of China.Using Landsat data,we calculated the Normalized Difference Vegetation Index(NDVI),Enhanced Vegetation Index(EVI),and kernel NDVI(kNDVI)for the ZLRB from 1990 to 2020.We analyzed the spatiotemporal variations of these VIs using trend analysis and the Mann-Kendall test,and quantified the contributions of climate change(considering time-lag effects)and human activities to VIs changes through wavelet and residual analyses.Results indicated that VIs generally exhibited an upward trend in the ZLRB,with significant improvements observed in 54.91% of the area for NDVI,31.69% for EVI,and 33.71% for kNDVI.Among them,NDVI outperformed EVI and kNDVI in capturing vegetation changes in the semi-arid area.VIs responded to precipitation with 1-month time lag and no time lag to temperature during growing season.Moreover,precipitation had a stronger positive correlation with VIs than temperature.Climate change was identified as the dominant driver of vegetation dynamics in the ZLRB,accounting for 93.12% of NDVI variation,while human activities contributed only 6.88%.Comparative analysis of VIs suggests that NDVI was more suitable for describing vegetation changes in the typical arid area of the ZLRB.Our findings underscore the importance of selecting appropriate VIs for targeted ecological restoration and sustainable land management.展开更多
Rapid urbanization and land-use changes are placing immense pressure on resources,infrastructure,and envi-ronmental sustainability.To address these,accurate urban simulation models are essential for sustainable develo...Rapid urbanization and land-use changes are placing immense pressure on resources,infrastructure,and envi-ronmental sustainability.To address these,accurate urban simulation models are essential for sustainable development and governance.Among them,Cellular Automata(CA)models have become key tools for pre-dicting urban expansion,optimizing land-use planning,and supporting data-driven decision-making.This review provides a comprehensive examination of the development of urban cellular automata(UCA)models,presenting a new framework to enhance individual UCA sub-modules within the context of emerging technologies,sus-tainable environments,and public governance.By addressing gaps in prior UCA modelling reviews-particularly in the integration and optimization of UCA sub-module technologies-this framework is designed to simplify UCA model understanding and development.We systematically review pioneering case studies,deconstruct current UCA operational processes,and explore modern technologies,such as big data and artificial intelligence,to optimize these sub-modules further.We discuss current limitations within UCA models and propose future pathways,emphasizing the necessity of comprehensive analyses for effective UCA simulations.Proposed solu-tions include strengthening our understanding of urban growth mechanisms,examining spatial positioning and temporal evolution dynamics,and enhancing urban geographic simulations with deep learning techniques to support sustainable transitions in public governance.These improvements offer data-driven decision support for environmental management,advancing policies that foster sustainable urban development.展开更多
There have been an increasing number of studies on climate change and population health over the past 20 years,with most focusing on health risk assessment,targeting different locations and populations with various di...There have been an increasing number of studies on climate change and population health over the past 20 years,with most focusing on health risk assessment,targeting different locations and populations with various diseases[1−2].While these studies have provided the necessary epidemiological evidence for health authorities in policymaking,it is time to develop and implement tailored health interventions to protect the health and well-being of communities,and particularly that of vulnerable groups.展开更多
Previous works were mainly concentrated on long-term average runoff alterations,and extreme temperatures and watershed conditions are little analyzed.In this study,we collected gauged river flow and meteorological dat...Previous works were mainly concentrated on long-term average runoff alterations,and extreme temperatures and watershed conditions are little analyzed.In this study,we collected gauged river flow and meteorological data time series from 1916 to 2015 and 1941 to 2015 across the contiguous United States(CONUS)for 188 catchments to investigate the temporal trends and spatial features of runoff changes at multi-time scales.We also analyzed the relationships between runoff changes and climatic factors.Median descriptive statistics and Budyko coupled climate elasticity methods were used to calculate runoff elasticity in each time scale.The original Mann-Kendall trend test was used to test their trend significance in four time-scale(11,20,40,and 60 a),respectively.The results show that the trend of runoff changes is more significant in high time scales;total changes are heterogeneous over CONUS.After the 1970s,increases of up to 27%decade-1 were mainly concentrated in the mid-northern regions.Maximum temperature and catchment characteristics are vital factors for runoff alteration;runoff changes are independent of rainfall,and wet regions tend to have lower changes.These findings could help develop better regional water resource planning and management.展开更多
South Florida’s natural forest ecosystems,including pine rocklands and hardwood hammocks,are threatened by land use change and urbanization,invasive species,and climate change.It is critical to understand the respons...South Florida’s natural forest ecosystems,including pine rocklands and hardwood hammocks,are threatened by land use change and urbanization,invasive species,and climate change.It is critical to understand the responses of these ecosystems to anthropogenic disturbances to conserve the remnants of the USA natural subtropical forests.Using dendrochronology,long-term growth patterns were characterized in three dominant native tree species:Bursera simaruba,Swietenia mahagoni,and Pinus elliottii.Core samples were collected from>30 individuals of each species in hardwood hammocks(B.simaruba and S.mahagoni)and pine rocklands(P.elliottii)to examine growth patterns.Relationships between annual tree growth rates and climatic variables were assessed to address three questions:(1)What are the climatic drivers of growth in these three South Florida tree species?(2)Are their growth rates stable or changing through time?and(3)Are tree growth rates affected by urbanization?Standardized growth rates of the three species have changed through time,with small young trees showing accelerated growth through time,whereas larger,older trees showed declining growth rates.S.mahagoni and B.simaruba grew faster in urbanized parks than in more natural parks,whereas P.elliottii grew slower in urban parks.There were positive correlations between tree growth and the current year’s fall precipitation and no discernable effects of the current year’s monthly temperatures on growth rates of any of the species.These results suggest that the foundational tree species of the southern USA endangered pine rocklands and hardwood hammocks may be vulnerable to ongoing changes in precipitation and temperature as well as other environmental effects associated with urbanization.展开更多
Two long-term slow slip events(SSEs) in Lower Cook Inlet, Alaska, were identified by Li SS et al.(2016). The earlier SSE lasted at least 9 years with M_(w) ~7.8 and had an average slip rate of ~82 mm/year. The latter ...Two long-term slow slip events(SSEs) in Lower Cook Inlet, Alaska, were identified by Li SS et al.(2016). The earlier SSE lasted at least 9 years with M_(w) ~7.8 and had an average slip rate of ~82 mm/year. The latter SSE, occurring in a similar area, lasted approximately 2 years with M_(w) ~7.2 and an average slip rate of ~91 mm/year. To test whether these SSEs triggered earthquakes near the slow slip area, we calculated the Coulomb stressing rate changes on receiver faults by using two fault geometry definitions: nodal planes of focal mechanism solutions of past earthquakes, and optimally oriented fault planes. Regions in the shallow slab(30–60 km) that experienced a significant increase in the Coulomb stressing rate due to slip by the SSEs showed an increase in seismicity rates during SSE periods. No correlation was found in the volumes that underwent a significant increase in the Coulomb stressing rate during the SSE within the crust and the intermediate slab. We modeled variations in seismicity rates by using a combination of the Coulomb stress transfer model and the framework of rate-and-state friction. Our model indicated that the SSEs increased the Coulomb stress changes on adjacent faults,thereby increasing the seismicity rates even though the ratio of the SSE stressing rate to the background stressing rate was small. Each long-term SSE in Alaska brought the megathrust updip of the SSE areas closer to failure by up to 0.1–0.15 MPa. The volumes of significant Coulomb stress changes caused by the Upper and Lower Cook Inlet SSEs did not overlap.展开更多
Understanding the complex relationship between vegetation change and both natural and anthropogenic factors is a subject of global importance.However,comprehensive explanations of vegetation cover trends across China...Understanding the complex relationship between vegetation change and both natural and anthropogenic factors is a subject of global importance.However,comprehensive explanations of vegetation cover trends across China’s different regions and the dynamic roles of their drivers remain limited.This study analyzed national and regional vegetation change trends from 2000 to 2020 and evaluated the evolving impacts of natural and anthropogenic factors.Results indicate that 44.14%of China’s land experienced significant increase(P<0.05)in vegetation coverage.The Northeast(A1),Southwest(A5),and South China(A8)regions showed extremely significant increases in vegetation cover,with over 65%of vegetation exhibiting extremely significant growth(P<0.01).In contrast,less than 25%of vegetation in Inner Mongolia(A2),Northwest(A3),and the Qinghai-Tibetan Plateau(A4)subregions demonstrated an extremely significant increasing trend(P<0.01).Precipitation(q=0.766)and land use type(q=0.636)were the most influential natural and anthropogenic factors,respectively,with their interaction(q=0.838)dominating national vegetation patterns.On the west side of the Hu Line,vegetation dynamics were mainly limited by arid and semi-arid climates,with precipitation as the dominant factor,though land use measures have contributed to some vegetation improvement.Between 2000 and 2020,the influence of precipitation on vegetation cover increased in regions A3 and A4,with q-values rising by 26.73%and 101.13%,respectively.Additionally,soil type exerted a significant effect(P<0.001)on vegetation cover across all regions,being most pronounced in A2(q=0.692).On the east side of the Hu Line,vegetation growth benefited generally from warm and humid conditions,while local decline in urbanized areas was largely attributable to land use change and economic expansion.Concurrently anthropogenic factors such as land use and population density increasingly influenced vegetation dynamics in eastern urban areas of the Hu Line.Population density and GDP were the most influential factors affecting vegetation cover in region A8,with q-values of 0.443 and 0.380,respectively(P<0.001).Future efforts should maintain the benefits of large-scale ecological projects and harmonize the relationship between urban vegetation and anthropogenic influences.展开更多
A robust ecological security network(ESN)is essential for ensuring regional ecological security,improving fragile ecological conditions,and promoting sustainable development.Climate change and land use/cover change(LU...A robust ecological security network(ESN)is essential for ensuring regional ecological security,improving fragile ecological conditions,and promoting sustainable development.Climate change and land use/cover change(LUCC)influence the structure and connectivity of the ESN by impacting ecosystem services(ESs).Previous studies primarily focused on the overall effects of LUCC on ESN changes,but they largely overlooked the effects of detailed LUCC transitions.In this study,we evaluated changes in the structure and connectivity of the ESN in the Songnen Plain(SNP),Northeast China,over the past 30 yr(1990s-2020s)using circuit theory and graph theory.We further explored the effects of climate change,LUCC,and detailed LUCC transformations on ESN changes through factorial control experiments.Results revealed a 24.86%decrease in ecological sources and a 27.06%decrease in ecological corridors,accompanied by a decline in ESN connectivity from the 1990s to the 2010s.Conversely,from the 2010s to the 2020s,ecological sources increased by 14.71%and ecological corridors increased by 25.71%due to ecological projects such as returning farmland to wetlands,resulting in an overall increase in ESN connectivity.The changes in ESN structure were primarily attributed to LUCC effects,followed by climate change effects and their interactions.In contrast,the changes in connectivity were significantly affected by climate change,followed by interactive effects and LUCC.Through detailed examination of LUCC transformation effects,we further found that the changes in ESN structure were primarily attributed to wetland loss,followed by deforestation and urban expansion.Meanwhile,the changes in ESN connectivity were mainly due to the effects of wetland loss,urban expansion and deforestation.Notably,the adverse effects of wetland loss partly offset climate change benefits on ESN.Our study offers valuable insights for developing future land management policies and implementing ecological projects,aimed at maintaining a stable ESN and ensuring sustainable human development.展开更多
Rapid climate and cropland use changes in recent decades have posed major challenges to food security in China.Hainan Is-land is the only tropical island in China and is blessed with natural conditions for crop produc...Rapid climate and cropland use changes in recent decades have posed major challenges to food security in China.Hainan Is-land is the only tropical island in China and is blessed with natural conditions for crop production.This study first simulates the climate scenarios of Hainan Island for 2030,2040 and 2050 under the four Socio-economic Pathways(SSPs)based on the climate models in ScenarioMIP of Coupled Model Intercomparison Project Phase 6(CMIP6),and then simulates the land use scenarios of Hainan Island for 2030,2040 and 2050 based on the Cellular Automata(CA)-Markov model.Finally,based on the Global Agro-Ecological Zones(GAEZ)model,the rice potential yield in Hainan Island for 2030,2040 and 2050 are simulated,and the effects of future climate and cropland use changes on rice potential yields are investigated.The results show that:1)from 2020 to 2050,mean maximum temperature first decreases and then increases,while mean minimum temperature increase sharply followed by a leveling off under the four SSPs.Precipitation decreases and then increases under other three SSPs except SSP2-4.5.Net solar radiation increases continuously under SSP1-2.6,2-4.5,and 5-8.5,and has the lowest simulated values under SSP3-7.0.Mean wind speed increases continuously under SSP1-2.6,fluctuates more under SSP2-4.5 and SSP5-8.5,and increases slowly and then decreases sharply under SSP3-7.0.Relative humidity basically decreases continuously under the four SSPs.2)Areas of paddy field are 302.49 thousand,302.41 thousand and 302.71 thou-sand ha for 2030,2040 and 2050,respectively,all less than that in 2020.Paddy field is mainly converted into built-up land and wood-land.As for the conversion of other land types to paddy field,woodland is the main source.3)Under the effects of future climate and cropland use changes,the mean potential productions in Hainan Island under the four SSPs increase 1.17 million,1.13 million and 1.11 million t,respectively,and the mean potential yields increase 3873.21,3766.71 and 3672.38 kg/ha,respectively for the three periods.The largest increases in mean rice potential production and mean potential yield are 1.21 million t and 4008.00 kg/ha,1.16 million t and 3846.65 kg/ha,as well as 1.13 million t and 3732.75 kg/ha,respectively under SSP 3-7.0,indicating that SSP3-7.0 is the most suitable scenario for rice growth.This study could provide scientific basis for crop planting planning and agricultural policy adjustment.展开更多
Renewable energy,especially solar power,is vital for mitigating global warming,while climate change also impacts solar photovoltaic potential(PVpot).This study analyzes historical(1985–2014)and future(2015–2100)clim...Renewable energy,especially solar power,is vital for mitigating global warming,while climate change also impacts solar photovoltaic potential(PVpot).This study analyzes historical(1985–2014)and future(2015–2100)climate effects on PVpot,and quantifies contributions from changed radiation,temperature,and wind speed.Historically,global PVpot increased by 0.42‰,with notable rises in eastern China(+7.1‰)and southern Europe(+3.5‰).By the end of the century,increased radiation-induced PVpot(+1.27‰)offsets temperatureinduced PVpot loss(−0.54‰)under SSP1-2.6,yielding a net PVpot increase(+0.74‰).Under SSP2-4.5,the temperature-induced PVpot decline(−1.50‰)drives the final PVpot reduction(−1.15‰).Under SSP3-7.0 and SSP5-8.5,combined radiation-induced(−1.94‰and−1.99‰)and temperature-induced PVpot changes(−2.67‰and−3.41‰)result in significant PVpot declines(−4.57‰and−5.31‰).Regional analysis reveals that eastern China(+0.7‰to+8.6‰),southern Europe(+0.3‰to+2.5‰),and Northwest South America(+0.6‰to+2.1‰)retain positive changes in future PVpot across all climate scenarios,which may be due to reduced aerosols and cloud cover,suggesting these areas can remain suitable for photovoltaic installations despite climate changes.In contrast,temperature-driven PVpot declines over the Qinghai-Tibet Plateau(−9.1‰to−4.3‰)and northern Africa(−9.3‰to−4.9‰)under future high-emission scenarios indicate that these historically advantageous regions will become less suitable for solar energy deployment.The findings underscore that climate changes driven by sustainable development pathways will generate more PVpot in the future for better global warming mitigation.展开更多
The Liaohe River Basin(LRB)in Northeast China,a critical agricultural and industrial zone,has faced escalating water resource pressures in recent decades due to rapid urbanization,intensified land use changes,and clim...The Liaohe River Basin(LRB)in Northeast China,a critical agricultural and industrial zone,has faced escalating water resource pressures in recent decades due to rapid urbanization,intensified land use changes,and climate variability.Understanding the spatiotemporal dynamics of water yield and its driving factors is essential for sustainable water resource management in this ecologically sensitive region.This study employed the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model to quantify the spatiotemporal patterns of water yield in the LRB(dividing into six sub-basins from east to west:East Liaohe River Basin(ELRB),Taizi River Basin(TRB),Middle Liaohe River Basin(MLRB),West Liaohe River Basin(WLRB),Xinkai River Basin(XRB),and Wulijimuren River Basin(WRB))from 1993 to 2022,with a focus on the impacts of climate change and land use cover change(LUCC).Results revealed that the LRB had an average annual precipitation of 483.15 mm,with an average annual water yield of 247.54 mm,both showing significant upward trend over the 30-a period.Spatially,water yield demonstrated significant heterogeneity,with higher values in southeastern sub-basins and lower values in northwestern sub-basins.The TRB exhibited the highest water yield due to abundant precipitation and favorable topography,while the WRB recorded the lowest water yield owing to arid conditions and sparse vegetation.Precipitation played a significant role in shaping the annual fluctuations and total volume of water yield,with its variability exerting substantially greater impacts than actual evapotranspiration(AET)and LUCC.However,LUCC,particularly cultivated land expansion and grassland reduction,significantly reshaped the spatial distribution of water yield by modifying surface runoff and infiltration patterns.This study provides critical insights into the spatiotemporal dynamics of water yield in the LRB,emphasizing the synergistic effects of climate change and land use change,which are pivotal for optimizing water resource management and advancing regional ecological conservation.展开更多
Change detection(CD)plays a crucial role in numerous fields,where both convolutional neural networks(CNNs)and Transformers have demonstrated exceptional performance in CD tasks.However,CNNs suffer from limited recepti...Change detection(CD)plays a crucial role in numerous fields,where both convolutional neural networks(CNNs)and Transformers have demonstrated exceptional performance in CD tasks.However,CNNs suffer from limited receptive fields,hindering their ability to capture global features,while Transformers are constrained by high computational complexity.Recently,Mamba architecture,which is based on state space models(SSMs),has shown powerful global modeling capabilities while achieving linear computational complexity.Although some researchers have incorporated Mamba into CD tasks,the existing Mamba⁃based remote sensing CD methods struggle to effectively perceive the inherent locality of changed regions when flattening and scanning remote sensing images,leading to limitations in extracting change features.To address these issues,we propose a novel Mamba⁃based CD method termed difference feature fusion Mamba model(DFFMamba)by mitigating the loss of feature locality caused by traditional Mamba⁃style scanning.Specifically,two distinct difference feature extraction modules are designed:Difference Mamba(DMamba)and local difference Mamba(LDMamba),where DMamba extracts difference features by calculating the difference in coefficient matrices between the state⁃space equations of the bi⁃temporal features.Building upon DMamba,LDMamba combines a locally adaptive state⁃space scanning(LASS)strategy to enhance feature locality so as to accurately extract difference features.Additionally,a fusion Mamba(FMamba)module is proposed,which employs a spatial⁃channel token modeling SSM(SCTMS)unit to integrate multi⁃dimensional spatio⁃temporal interactions of change features,thereby capturing their dependencies across both spatial and channel dimensions.To verify the effectiveness of the proposed DFFMamba,extensive experiments are conducted on three datasets of WHU⁃CD,LEVIR⁃CD,and CLCD.The results demonstrate that DFFMamba significantly outperforms state⁃of⁃the⁃art CD methods,achieving intersection over union(IoU)scores of 90.67%,85.04%,and 66.56%on the three datasets,respectively.展开更多
文摘We examine possible funding sources for constructing Climate Change Haven Communities on a global basis. Areas of the planet that have the potential to house persons migrating to “safe havens” in their own or other countries will require the rapid construction of communities capable of supporting them, their families, businesses and farms. However, different political-economic conditions are found across the areas which can serve as locations for these Climate Change Haven Communities. We develop funding and construction strategies for the United States (free-market capitalism), France and Spain (European Union supported economies), and Taiwan region (state-directed economy). The proposals for the Taiwan region should also be applicable to the rest of China.
基金Supported by the Scientific Research Projects of the Health System in Pingshan District,No.2023122.
文摘BACKGROUND Lumbar interbody fusion(LIF)is the primary treatment for lumbar degenerative diseases.Elderly patients are prone to anxiety and depression after undergoing surgery,which affects their postoperative recovery speed and quality of life.Effective prevention of anxiety and depression in elderly patients has become an urgent problem.AIM To investigate the trajectory of anxiety and depression levels in elderly patients after LIF,and the influencing factors.METHODS Random sampling was used to select 239 elderly patients who underwent LIF from January 2020 to December 2024 in Shenzhen Pingle Orthopedic Hospital.General information and surgery-related indices were recorded,and participants completed measures of psychological status,lumbar spine dysfunction,and quality of life.A latent class growth model was used to analyze the post-LIF trajectory of anxiety and depression levels,and unordered multi-categorical logistic regression was used to analyze the influencing factors.RESULTS Three trajectories of change in anxiety level were identified:Increasing anxiety(n=26,10.88%),decreasing anxiety(n=27,11.30%),and stable anxiety(n=186,77.82%).Likewise,three trajectories of change in depression level were identified:Increasing depression(n=30,12.55%),decreasing depression(n=26,10.88%),and stable depression(n=183,76.57%).Regression analysis showed that having no partner,female sex,elevated Oswestry dysfunction index(ODI)scores,and reduced 36-Item Short Form Health Survey scores all contributed to increased anxiety levels,whereas female sex,postoperative opioid use,and elevated ODI scores all contributed to increased depression levels.CONCLUSION During clinical observation,combining factors to predict anxiety and depression in post-LIF elderly patients enables timely intervention,quickens recovery,and enhances quality of life.
基金supported by the Henan Province Key R&D Project under Grant 241111210400the Henan Provincial Science and Technology Research Project under Grants 252102211047,252102211062,252102211055 and 232102210069+2 种基金the Jiangsu Provincial Scheme Double Initiative Plan JSS-CBS20230474,the XJTLU RDF-21-02-008the Science and Technology Innovation Project of Zhengzhou University of Light Industry under Grant 23XNKJTD0205the Higher Education Teaching Reform Research and Practice Project of Henan Province under Grant 2024SJGLX0126。
文摘Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectral similarity between buildings and backgrounds,sensor variations,and insufficient computational efficiency.To address these challenges,this paper proposes a novel Multi-scale Efficient Wavelet-based Change Detection Network(MewCDNet),which integrates the advantages of Convolutional Neural Networks and Transformers,balances computational costs,and achieves high-performance building change detection.The network employs EfficientNet-B4 as the backbone for hierarchical feature extraction,integrates multi-level feature maps through a multi-scale fusion strategy,and incorporates two key modules:Cross-temporal Difference Detection(CTDD)and Cross-scale Wavelet Refinement(CSWR).CTDD adopts a dual-branch architecture that combines pixel-wise differencing with semanticaware Euclidean distance weighting to enhance the distinction between true changes and background noise.CSWR integrates Haar-based Discrete Wavelet Transform with multi-head cross-attention mechanisms,enabling cross-scale feature fusion while significantly improving edge localization and suppressing spurious changes.Extensive experiments on four benchmark datasets demonstrate MewCDNet’s superiority over comparison methods:achieving F1 scores of 91.54%on LEVIR,93.70%on WHUCD,and 64.96%on S2Looking for building change detection.Furthermore,MewCDNet exhibits optimal performance on the multi-class⋅SYSU dataset(F1:82.71%),highlighting its exceptional generalization capability.
基金The National University of Mongolia,No.P2024-4814The Mongolian Science and Technology Foundation,No.CHN-2022/274The‘Chey Institute for Advanced Studies’International Scholar Exchange Fellowship for the Academic Year of 2025-2026。
文摘This study investigates climate-and human-induced hydrological changes in the Zavkhan River-Khyargas Lake Basin,a highly sensitive arid and semi-arid region of Central Asia.Using Mann-Kendall,innovative trend analysis,and Sen's slope estimation methods,historical climate trends(1980-2100)were analyzed,while land cover changes represented human impacts.Future projections were simulated using the MIROC model with Shared Socioeconomic Pathways(SSPs)and the Tank model.Results show that during the past 40 years,air temperature significantly increased(Z=3.93^(***)),while precipitation(Z=-1.54^(*))and river flow(Z=-1.73^(*))both declined.The Khyargas Lake water level dropped markedly(Z=-5.57***).Land cover analysis reveals expanded cropland and impervious areas due to human activity.Under the SSP1.26 scenario,which assumes minimal climate change,air temperature is projected to rise by 2.0℃,precipitation by 21.8 mm,and river discharge by 1.61 m^(3)/s between 2000 and 2100.These findings indicate that both global warming and intensified land use have substantially altered hydrological and climatic processes in the basin,highlighting the vulnerability of western Mongolia's water resources to combined climatic and anthropogenic influence.
基金supported by the Laoshan Laboratory[grant number LSKJ202202403]the National Natural Science Foundation of China[grant number 42030410]+1 种基金additionally supported by the Startup Foundation for Introducing Talent of NUISTJiangsu Innovation Research Group[grant number JSSCTD202346]。
文摘Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diverse sensitivities of surface fluxes.This study utilizes data from the Flux-Anomaly-Forced Model Intercomparison Project to investigate how ocean salinity responds to perturbations of surface fluxes.The findings indicate the emergence of a sea surface salinity(SSS)dipole pattern predominantly in the North Atlantic and Pacific fresh pools,driven by surface flux perturbations.This results in an intensification of the“salty gets saltier and fresh gets fresher”SSS pattern across the global ocean.The spatial pattern amplification(PA)of SSS under global warming is estimated to be approximately 11.5%,with surface water flux perturbations being the most significant contributor to salinity PA,accounting for 8.1% of the change after 70 years in experiments since pre-industrial control(piControl).Notably,the zonal-depth distribution of salinity in the upper ocean exhibits lighter seawater above the denser water,with bowed isopycnals in the upper 400 m.This stable stratification inhibits vertical mixing of salinity and temperature.In response to the flux perturbations,there is a strong positive feedback due to consequent freshening.It is hypothesized that under global warming,an SSS amplification of 7.2%/℃ and a mixed-layer depth amplification of 12.5%/℃ will occur in the global ocean.It suggests that the salinity effect can exert a more stable ocean to hinder the downward transfer of heat,which provides positive feedback to future global warming.
文摘To address climate change and highlight its global nature,the United Nations Framework Convention on Climate Change(UNFCCC)was adopted for the first time in history within the UN framework on May 9,1992,clearly establishing the obligations of developed countries to take the lead in emission reduction and provide financial,technological,and capacity-building support to developing countries.Particularly since the 2015 Paris Agreement,successive UN climate conferences have placed high emphasis on financial and technological matters,with financial arrangements demonstrating an increasingly specific trend in recent years.The Glasgow Climate Pact adopted in 2021 urges developed country Parties to deliver on their commitment to the goal of providing USD 100 billion to developing country prties,while also urging developed country parties to at least double their provision of climate finance to developing country parties by 2025 compared to 2019 levels.
基金Key Project of National Social Science Fund,No.23AZD032National Natural Science Foundation of China No.42371258Program of China Scholarship Council No.202306850036。
文摘Low-carbon urban development in China can pave the way to achieve the dualcarbon goal.Exploring how land use changes(LUCs)impact carbon storage(CS)under multi-climate scenarios in different urban agglomerations helps to formulate differential scientific carbon mitigation policies.In this regard,this study constructs an integrated model of SD-PLUS-InVEST to simulate LUCs and CS changes under multi-climate change-based scenarios(SSP126,SSP245,SSP585)for three major urban agglomerations(3UAs)in the Yangtze River Economic Belt.Results demonstrate that land use demand in the 3UAs changes considerably in each scenario.Construction land in the 3UAs remains the most important growth category for the coming decade,but its increase varies in different scenarios.CS in the Yangtze River Delta Urban Agglomeration(YRDUA)and Mid-Yangtze River Urban Agglomeration(MYRUA)shows a similar downward trend under different scenarios,with scenario SSP245 decreasing the most,to 184,713.526 Tg and 384,459.729 Tg,respectively.CS in the Cheng-Yu(Chengdu-Chongqing)Urban Agglomeration(CYUA)exhibits the opposite upward trend,with scenario SSP126 increasing the most to 153,007.973 Tg.The major cause of CS loss remains the conversion of forest land to construction land in the YRDUA and MYRUA under different scenarios.However,in the CYUA,the conversion of forest land to cultivated land is the major driver of CS loss under scenario SSP126.In contrast,the conversion of cultivated land to construction land dominantly drives CS loss under scenarios SSP245 and SSP585.The conversion of water body to other land use types is the major cause of CS gain in the YRDUA and MYRUA under different scenarios.At the same time,in the CYUA,the driver is the conversion of cultivated land to forest land.These findings demonstrate the significance of the low-carbon development in urban agglomerations at different development stages at home and abroad.
基金funded by the National Natural Science Foundation of China(U21A2011).
文摘Climate warming and humidification trends have significantly influenced vegetation growth patterns in Chinese semi-arid areas.Exploring vegetation dynamics is crucial for understanding regional ecosystem structure and improving the efforts of ecosystem restoration.However,the applicability of various vegetation indices(VIs)in these arid areas remains uncertain.Evaluating the applicability of multiple VIs for vegetation monitoring can elucidate the variability of VIs performance at regional scale.Therefore,this study selected the Zuli River Basin(ZLRB),a typical loess hilly watershed in the semi-arid areas of China.Using Landsat data,we calculated the Normalized Difference Vegetation Index(NDVI),Enhanced Vegetation Index(EVI),and kernel NDVI(kNDVI)for the ZLRB from 1990 to 2020.We analyzed the spatiotemporal variations of these VIs using trend analysis and the Mann-Kendall test,and quantified the contributions of climate change(considering time-lag effects)and human activities to VIs changes through wavelet and residual analyses.Results indicated that VIs generally exhibited an upward trend in the ZLRB,with significant improvements observed in 54.91% of the area for NDVI,31.69% for EVI,and 33.71% for kNDVI.Among them,NDVI outperformed EVI and kNDVI in capturing vegetation changes in the semi-arid area.VIs responded to precipitation with 1-month time lag and no time lag to temperature during growing season.Moreover,precipitation had a stronger positive correlation with VIs than temperature.Climate change was identified as the dominant driver of vegetation dynamics in the ZLRB,accounting for 93.12% of NDVI variation,while human activities contributed only 6.88%.Comparative analysis of VIs suggests that NDVI was more suitable for describing vegetation changes in the typical arid area of the ZLRB.Our findings underscore the importance of selecting appropriate VIs for targeted ecological restoration and sustainable land management.
文摘Rapid urbanization and land-use changes are placing immense pressure on resources,infrastructure,and envi-ronmental sustainability.To address these,accurate urban simulation models are essential for sustainable development and governance.Among them,Cellular Automata(CA)models have become key tools for pre-dicting urban expansion,optimizing land-use planning,and supporting data-driven decision-making.This review provides a comprehensive examination of the development of urban cellular automata(UCA)models,presenting a new framework to enhance individual UCA sub-modules within the context of emerging technologies,sus-tainable environments,and public governance.By addressing gaps in prior UCA modelling reviews-particularly in the integration and optimization of UCA sub-module technologies-this framework is designed to simplify UCA model understanding and development.We systematically review pioneering case studies,deconstruct current UCA operational processes,and explore modern technologies,such as big data and artificial intelligence,to optimize these sub-modules further.We discuss current limitations within UCA models and propose future pathways,emphasizing the necessity of comprehensive analyses for effective UCA simulations.Proposed solu-tions include strengthening our understanding of urban growth mechanisms,examining spatial positioning and temporal evolution dynamics,and enhancing urban geographic simulations with deep learning techniques to support sustainable transitions in public governance.These improvements offer data-driven decision support for environmental management,advancing policies that foster sustainable urban development.
文摘There have been an increasing number of studies on climate change and population health over the past 20 years,with most focusing on health risk assessment,targeting different locations and populations with various diseases[1−2].While these studies have provided the necessary epidemiological evidence for health authorities in policymaking,it is time to develop and implement tailored health interventions to protect the health and well-being of communities,and particularly that of vulnerable groups.
基金supported by National Key R&D Program of China(No.2018YFC0407303)“Young Talents”Project of Northeast Agricultural University(No.20QC13)the Natural Science Foundation of Heilongjiang Province of China(No.E2017009)。
文摘Previous works were mainly concentrated on long-term average runoff alterations,and extreme temperatures and watershed conditions are little analyzed.In this study,we collected gauged river flow and meteorological data time series from 1916 to 2015 and 1941 to 2015 across the contiguous United States(CONUS)for 188 catchments to investigate the temporal trends and spatial features of runoff changes at multi-time scales.We also analyzed the relationships between runoff changes and climatic factors.Median descriptive statistics and Budyko coupled climate elasticity methods were used to calculate runoff elasticity in each time scale.The original Mann-Kendall trend test was used to test their trend significance in four time-scale(11,20,40,and 60 a),respectively.The results show that the trend of runoff changes is more significant in high time scales;total changes are heterogeneous over CONUS.After the 1970s,increases of up to 27%decade-1 were mainly concentrated in the mid-northern regions.Maximum temperature and catchment characteristics are vital factors for runoff alteration;runoff changes are independent of rainfall,and wet regions tend to have lower changes.These findings could help develop better regional water resource planning and management.
基金supported by the Kushlan Fund from the University of Miami Department of Biology.
文摘South Florida’s natural forest ecosystems,including pine rocklands and hardwood hammocks,are threatened by land use change and urbanization,invasive species,and climate change.It is critical to understand the responses of these ecosystems to anthropogenic disturbances to conserve the remnants of the USA natural subtropical forests.Using dendrochronology,long-term growth patterns were characterized in three dominant native tree species:Bursera simaruba,Swietenia mahagoni,and Pinus elliottii.Core samples were collected from>30 individuals of each species in hardwood hammocks(B.simaruba and S.mahagoni)and pine rocklands(P.elliottii)to examine growth patterns.Relationships between annual tree growth rates and climatic variables were assessed to address three questions:(1)What are the climatic drivers of growth in these three South Florida tree species?(2)Are their growth rates stable or changing through time?and(3)Are tree growth rates affected by urbanization?Standardized growth rates of the three species have changed through time,with small young trees showing accelerated growth through time,whereas larger,older trees showed declining growth rates.S.mahagoni and B.simaruba grew faster in urbanized parks than in more natural parks,whereas P.elliottii grew slower in urban parks.There were positive correlations between tree growth and the current year’s fall precipitation and no discernable effects of the current year’s monthly temperatures on growth rates of any of the species.These results suggest that the foundational tree species of the southern USA endangered pine rocklands and hardwood hammocks may be vulnerable to ongoing changes in precipitation and temperature as well as other environmental effects associated with urbanization.
基金supported by the National Natural Science Foundation of China (Grant No. 42104001)。
文摘Two long-term slow slip events(SSEs) in Lower Cook Inlet, Alaska, were identified by Li SS et al.(2016). The earlier SSE lasted at least 9 years with M_(w) ~7.8 and had an average slip rate of ~82 mm/year. The latter SSE, occurring in a similar area, lasted approximately 2 years with M_(w) ~7.2 and an average slip rate of ~91 mm/year. To test whether these SSEs triggered earthquakes near the slow slip area, we calculated the Coulomb stressing rate changes on receiver faults by using two fault geometry definitions: nodal planes of focal mechanism solutions of past earthquakes, and optimally oriented fault planes. Regions in the shallow slab(30–60 km) that experienced a significant increase in the Coulomb stressing rate due to slip by the SSEs showed an increase in seismicity rates during SSE periods. No correlation was found in the volumes that underwent a significant increase in the Coulomb stressing rate during the SSE within the crust and the intermediate slab. We modeled variations in seismicity rates by using a combination of the Coulomb stress transfer model and the framework of rate-and-state friction. Our model indicated that the SSEs increased the Coulomb stress changes on adjacent faults,thereby increasing the seismicity rates even though the ratio of the SSE stressing rate to the background stressing rate was small. Each long-term SSE in Alaska brought the megathrust updip of the SSE areas closer to failure by up to 0.1–0.15 MPa. The volumes of significant Coulomb stress changes caused by the Upper and Lower Cook Inlet SSEs did not overlap.
基金Under the auspices of the National Natural Science Foundation of China(No.32371863)Fundamental Research Funds for the Central Universities(No.2572025AW39)。
文摘Understanding the complex relationship between vegetation change and both natural and anthropogenic factors is a subject of global importance.However,comprehensive explanations of vegetation cover trends across China’s different regions and the dynamic roles of their drivers remain limited.This study analyzed national and regional vegetation change trends from 2000 to 2020 and evaluated the evolving impacts of natural and anthropogenic factors.Results indicate that 44.14%of China’s land experienced significant increase(P<0.05)in vegetation coverage.The Northeast(A1),Southwest(A5),and South China(A8)regions showed extremely significant increases in vegetation cover,with over 65%of vegetation exhibiting extremely significant growth(P<0.01).In contrast,less than 25%of vegetation in Inner Mongolia(A2),Northwest(A3),and the Qinghai-Tibetan Plateau(A4)subregions demonstrated an extremely significant increasing trend(P<0.01).Precipitation(q=0.766)and land use type(q=0.636)were the most influential natural and anthropogenic factors,respectively,with their interaction(q=0.838)dominating national vegetation patterns.On the west side of the Hu Line,vegetation dynamics were mainly limited by arid and semi-arid climates,with precipitation as the dominant factor,though land use measures have contributed to some vegetation improvement.Between 2000 and 2020,the influence of precipitation on vegetation cover increased in regions A3 and A4,with q-values rising by 26.73%and 101.13%,respectively.Additionally,soil type exerted a significant effect(P<0.001)on vegetation cover across all regions,being most pronounced in A2(q=0.692).On the east side of the Hu Line,vegetation growth benefited generally from warm and humid conditions,while local decline in urbanized areas was largely attributable to land use change and economic expansion.Concurrently anthropogenic factors such as land use and population density increasingly influenced vegetation dynamics in eastern urban areas of the Hu Line.Population density and GDP were the most influential factors affecting vegetation cover in region A8,with q-values of 0.443 and 0.380,respectively(P<0.001).Future efforts should maintain the benefits of large-scale ecological projects and harmonize the relationship between urban vegetation and anthropogenic influences.
基金Under the auspices of National Key Research and Development Program of China(No.2022YFF1300904)the National Natural Science Foundation of China(No.42271119,42371075,42471127)+1 种基金Youth Innovation Promotion Association,Chinese Academy of Sciences(No.2023238)Jilin Province Science and Technology Development Plan Project(No.20230203001SF)。
文摘A robust ecological security network(ESN)is essential for ensuring regional ecological security,improving fragile ecological conditions,and promoting sustainable development.Climate change and land use/cover change(LUCC)influence the structure and connectivity of the ESN by impacting ecosystem services(ESs).Previous studies primarily focused on the overall effects of LUCC on ESN changes,but they largely overlooked the effects of detailed LUCC transitions.In this study,we evaluated changes in the structure and connectivity of the ESN in the Songnen Plain(SNP),Northeast China,over the past 30 yr(1990s-2020s)using circuit theory and graph theory.We further explored the effects of climate change,LUCC,and detailed LUCC transformations on ESN changes through factorial control experiments.Results revealed a 24.86%decrease in ecological sources and a 27.06%decrease in ecological corridors,accompanied by a decline in ESN connectivity from the 1990s to the 2010s.Conversely,from the 2010s to the 2020s,ecological sources increased by 14.71%and ecological corridors increased by 25.71%due to ecological projects such as returning farmland to wetlands,resulting in an overall increase in ESN connectivity.The changes in ESN structure were primarily attributed to LUCC effects,followed by climate change effects and their interactions.In contrast,the changes in connectivity were significantly affected by climate change,followed by interactive effects and LUCC.Through detailed examination of LUCC transformation effects,we further found that the changes in ESN structure were primarily attributed to wetland loss,followed by deforestation and urban expansion.Meanwhile,the changes in ESN connectivity were mainly due to the effects of wetland loss,urban expansion and deforestation.Notably,the adverse effects of wetland loss partly offset climate change benefits on ESN.Our study offers valuable insights for developing future land management policies and implementing ecological projects,aimed at maintaining a stable ESN and ensuring sustainable human development.
基金Under the auspices of Hainan Provincial Natural Science Foundation of China(No.321QN187,723RC466)Scientific Research Foundation of Hainan University(No.kyqd(sk)2135)Young Scholars Support Program of Hainan University(No.24QNFC-05)。
文摘Rapid climate and cropland use changes in recent decades have posed major challenges to food security in China.Hainan Is-land is the only tropical island in China and is blessed with natural conditions for crop production.This study first simulates the climate scenarios of Hainan Island for 2030,2040 and 2050 under the four Socio-economic Pathways(SSPs)based on the climate models in ScenarioMIP of Coupled Model Intercomparison Project Phase 6(CMIP6),and then simulates the land use scenarios of Hainan Island for 2030,2040 and 2050 based on the Cellular Automata(CA)-Markov model.Finally,based on the Global Agro-Ecological Zones(GAEZ)model,the rice potential yield in Hainan Island for 2030,2040 and 2050 are simulated,and the effects of future climate and cropland use changes on rice potential yields are investigated.The results show that:1)from 2020 to 2050,mean maximum temperature first decreases and then increases,while mean minimum temperature increase sharply followed by a leveling off under the four SSPs.Precipitation decreases and then increases under other three SSPs except SSP2-4.5.Net solar radiation increases continuously under SSP1-2.6,2-4.5,and 5-8.5,and has the lowest simulated values under SSP3-7.0.Mean wind speed increases continuously under SSP1-2.6,fluctuates more under SSP2-4.5 and SSP5-8.5,and increases slowly and then decreases sharply under SSP3-7.0.Relative humidity basically decreases continuously under the four SSPs.2)Areas of paddy field are 302.49 thousand,302.41 thousand and 302.71 thou-sand ha for 2030,2040 and 2050,respectively,all less than that in 2020.Paddy field is mainly converted into built-up land and wood-land.As for the conversion of other land types to paddy field,woodland is the main source.3)Under the effects of future climate and cropland use changes,the mean potential productions in Hainan Island under the four SSPs increase 1.17 million,1.13 million and 1.11 million t,respectively,and the mean potential yields increase 3873.21,3766.71 and 3672.38 kg/ha,respectively for the three periods.The largest increases in mean rice potential production and mean potential yield are 1.21 million t and 4008.00 kg/ha,1.16 million t and 3846.65 kg/ha,as well as 1.13 million t and 3732.75 kg/ha,respectively under SSP 3-7.0,indicating that SSP3-7.0 is the most suitable scenario for rice growth.This study could provide scientific basis for crop planting planning and agricultural policy adjustment.
基金supported by the Natural Science Foundation of Jiangsu Province[grant number BK20220031]the National Natural Science Foundation of China[grant number 42007195].
文摘Renewable energy,especially solar power,is vital for mitigating global warming,while climate change also impacts solar photovoltaic potential(PVpot).This study analyzes historical(1985–2014)and future(2015–2100)climate effects on PVpot,and quantifies contributions from changed radiation,temperature,and wind speed.Historically,global PVpot increased by 0.42‰,with notable rises in eastern China(+7.1‰)and southern Europe(+3.5‰).By the end of the century,increased radiation-induced PVpot(+1.27‰)offsets temperatureinduced PVpot loss(−0.54‰)under SSP1-2.6,yielding a net PVpot increase(+0.74‰).Under SSP2-4.5,the temperature-induced PVpot decline(−1.50‰)drives the final PVpot reduction(−1.15‰).Under SSP3-7.0 and SSP5-8.5,combined radiation-induced(−1.94‰and−1.99‰)and temperature-induced PVpot changes(−2.67‰and−3.41‰)result in significant PVpot declines(−4.57‰and−5.31‰).Regional analysis reveals that eastern China(+0.7‰to+8.6‰),southern Europe(+0.3‰to+2.5‰),and Northwest South America(+0.6‰to+2.1‰)retain positive changes in future PVpot across all climate scenarios,which may be due to reduced aerosols and cloud cover,suggesting these areas can remain suitable for photovoltaic installations despite climate changes.In contrast,temperature-driven PVpot declines over the Qinghai-Tibet Plateau(−9.1‰to−4.3‰)and northern Africa(−9.3‰to−4.9‰)under future high-emission scenarios indicate that these historically advantageous regions will become less suitable for solar energy deployment.The findings underscore that climate changes driven by sustainable development pathways will generate more PVpot in the future for better global warming mitigation.
基金funded by the Liaoning Provincial Social Science Planning Fund(L22AYJ010).
文摘The Liaohe River Basin(LRB)in Northeast China,a critical agricultural and industrial zone,has faced escalating water resource pressures in recent decades due to rapid urbanization,intensified land use changes,and climate variability.Understanding the spatiotemporal dynamics of water yield and its driving factors is essential for sustainable water resource management in this ecologically sensitive region.This study employed the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model to quantify the spatiotemporal patterns of water yield in the LRB(dividing into six sub-basins from east to west:East Liaohe River Basin(ELRB),Taizi River Basin(TRB),Middle Liaohe River Basin(MLRB),West Liaohe River Basin(WLRB),Xinkai River Basin(XRB),and Wulijimuren River Basin(WRB))from 1993 to 2022,with a focus on the impacts of climate change and land use cover change(LUCC).Results revealed that the LRB had an average annual precipitation of 483.15 mm,with an average annual water yield of 247.54 mm,both showing significant upward trend over the 30-a period.Spatially,water yield demonstrated significant heterogeneity,with higher values in southeastern sub-basins and lower values in northwestern sub-basins.The TRB exhibited the highest water yield due to abundant precipitation and favorable topography,while the WRB recorded the lowest water yield owing to arid conditions and sparse vegetation.Precipitation played a significant role in shaping the annual fluctuations and total volume of water yield,with its variability exerting substantially greater impacts than actual evapotranspiration(AET)and LUCC.However,LUCC,particularly cultivated land expansion and grassland reduction,significantly reshaped the spatial distribution of water yield by modifying surface runoff and infiltration patterns.This study provides critical insights into the spatiotemporal dynamics of water yield in the LRB,emphasizing the synergistic effects of climate change and land use change,which are pivotal for optimizing water resource management and advancing regional ecological conservation.
基金supported by the National Natural Science Foundation of China(Nos.42371449,41801386).
文摘Change detection(CD)plays a crucial role in numerous fields,where both convolutional neural networks(CNNs)and Transformers have demonstrated exceptional performance in CD tasks.However,CNNs suffer from limited receptive fields,hindering their ability to capture global features,while Transformers are constrained by high computational complexity.Recently,Mamba architecture,which is based on state space models(SSMs),has shown powerful global modeling capabilities while achieving linear computational complexity.Although some researchers have incorporated Mamba into CD tasks,the existing Mamba⁃based remote sensing CD methods struggle to effectively perceive the inherent locality of changed regions when flattening and scanning remote sensing images,leading to limitations in extracting change features.To address these issues,we propose a novel Mamba⁃based CD method termed difference feature fusion Mamba model(DFFMamba)by mitigating the loss of feature locality caused by traditional Mamba⁃style scanning.Specifically,two distinct difference feature extraction modules are designed:Difference Mamba(DMamba)and local difference Mamba(LDMamba),where DMamba extracts difference features by calculating the difference in coefficient matrices between the state⁃space equations of the bi⁃temporal features.Building upon DMamba,LDMamba combines a locally adaptive state⁃space scanning(LASS)strategy to enhance feature locality so as to accurately extract difference features.Additionally,a fusion Mamba(FMamba)module is proposed,which employs a spatial⁃channel token modeling SSM(SCTMS)unit to integrate multi⁃dimensional spatio⁃temporal interactions of change features,thereby capturing their dependencies across both spatial and channel dimensions.To verify the effectiveness of the proposed DFFMamba,extensive experiments are conducted on three datasets of WHU⁃CD,LEVIR⁃CD,and CLCD.The results demonstrate that DFFMamba significantly outperforms state⁃of⁃the⁃art CD methods,achieving intersection over union(IoU)scores of 90.67%,85.04%,and 66.56%on the three datasets,respectively.
