This paper investigates ruin,capital injection,and dividends for a two-dimensional risk model.The model posits that surplus levels of insurance companies are governed by a perturbed composite Poisson risk model.This m...This paper investigates ruin,capital injection,and dividends for a two-dimensional risk model.The model posits that surplus levels of insurance companies are governed by a perturbed composite Poisson risk model.This model introduces a dependence between the two surplus levels,present in both the associated perturbations and the claims resulting from common shocks.Critical levels of capital injection and dividends are established for each of the two risks.The surplus levels are observed discretely at fixed intervals,guiding decisions on capital injection,dividends,and ruin at these junctures.This study employs a two-dimensional Fourier cosine series expansion method to approximate the finite time expected discounted operating cost until ruin.The ensuing approximation error is also quantified.The validity and accuracy of the method are corroborated through numerical examples.Furthermore,the research delves into the optimal capital allocation problem.展开更多
A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and...A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and development of the NMI model and then emphasize that the NMI model represents a new tool for identifying the basic physics of how climate change influences mid-to-high latitude weather extremes.The building of the NMI model took place over three main periods.In the 1990s,a nonlinear Schr?dinger(NLS)equation model was presented to describe atmospheric blocking as a wave packet;however,it could not depict the lifetime(10-20 days)of atmospheric blocking.In the 2000s,we proposed an NMI model of atmospheric blocking in a uniform basic flow by making a scale-separation assumption and deriving an eddyforced NLS equation.This model succeeded in describing the life cycle of atmospheric blocking.In the 2020s,the NMI model was extended to include the impact of a changing climate mainly by altering the basic zonal winds and the magnitude of the meridional background potential vorticity gradient(PVy).Model results show that when PVy is smaller,blocking has a weaker dispersion and a stronger nonlinearity,so blocking can be more persistent and have a larger zonal scale and weaker eastward movement,thus favoring stronger weather extremes.However,when PVy is much smaller and below a critical threshold under much stronger winter Arctic warming of global warming,atmospheric blocking becomes locally less persistent and shows a much stronger westward movement,which acts to inhibit local cold extremes.Such a case does not happen in summer under global warming because PVy fails to fall below the critical threshold.Thus,our theory indicates that global warming can render summer-blocking anticyclones and mid-to-high latitude heatwaves more persistent,intense,and widespread.展开更多
In recent decades,large ensemble simulation(LENS)or super-large ensemble simulation(SLENS)experiments with climate models,including the simulation of both the historical and future climate,have been increasingly explo...In recent decades,large ensemble simulation(LENS)or super-large ensemble simulation(SLENS)experiments with climate models,including the simulation of both the historical and future climate,have been increasingly exploited in the fields of climate change,climate variability,climate projection,and beyond.This paper provides an overview of LENS in climate systems.It delves into its definition,initialization,significance,and scientific concerns.Additionally,its development history and relevant theories,methods,and primary fields of application are also reviewed.Conclusions obtained from single-model LENS can be more robust compared with those from ensemble simulations with smaller numbers of members.The interactions among model biases,forced responses,and internal variabilities,which serve as the added value in LENS,are highlighted.Finally,we put forward the future trajectory of LENS with climate or Earth system models(ESMs).Super-large ensemble simulation,high-resolution LENS,LENS employing ESMs,and combining LENS with artificial intelligence,will greatly promote the study of climate and related applications.展开更多
Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subs...Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subsequent impact on urban structure.Considering the varying travel costs associated with electric and fuel vehicles,we analyze the dynamic choices of households concerning house locations and vehicle types in a two-dimensional monocentric city.A spatial equilibrium is developed to model the interactions between urban density,vehicle age and vehicle type.An agent-based microeconomic residential choice model dynamically coupled with a house rent market is developed to analyze household choices of home locations and vehicle energy types,considering vehicle ages and competition for public charging piles.Key findings from our proposed models show that the proportion of electric vehicles(EVs)peaks at over 50%by the end of the first scrappage period,accompanied by more than a 40%increase in commuting distance and time compared to the scenario with only fuel vehicles.Simulation experiments on a theoretical grid indicate that heterogeneity-induced residential segregation can lead to urban sprawl and congestion.Furthermore,households with EVs tend to be located farther from the city center,and an increase in EV ownership contributes to urban expansion.Our study provides insights into how individuals adapt to EV transitions and the resulting impacts on home locations and land use changes.It offers a novel perspective on the dynamic interactions between EV adoption and urban development.展开更多
The influence of global climate change on endangered species is of growing concern, especially for rosewood species that are in urgent need of protection and restoration. Ecological niche models are commonly used to e...The influence of global climate change on endangered species is of growing concern, especially for rosewood species that are in urgent need of protection and restoration. Ecological niche models are commonly used to evaluate probable species’ distribution under climate change and contribute to decision-making to define efficient management strategies. A model was developed to forecast which habitat was most likely appropriate for the Dalbergia odorifera. We screened the main climatic variables that describe the current geographic distribution of the species based on maximum entropy modelling (Maxent). We subsequently assessed its potential future distribution under moderate (RCP2.6) and severe (RCP8.5) climate change scenarios for the years 2050 and 2070. The precipitation ranges of the wettest month and the warmest quarter are the primary limiting factors for the current distribution of D. odorifera among the climatic predictors. Climate change will be expected to have beneficial effects on the distribution range of D. odorifera. In conclusion, the main limits for the distribution of D. odorifera are determined by the level of precipitation and human activities. The results of this study indicate that the coasts of southern China and Chongqing will play a key role in the protection and restoration of D. odorifera in the future.展开更多
Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this st...Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this study,a Localized Error Subspace Transform Kalman Filter is employed in a coupled climate system model(the Flexible Global Ocean–Atmosphere–Land System Model,version f3-L(FGOALS-f3-L))to assimilate sea-ice concentration(SIC)and sea-ice thickness(SIT)data for melting-season ice predictions.The scheme is applied through the following steps:(1)initialization for generating initial ensembles;(2)analysis for assimilating observed data;(3)adoption for dividing ice states into five thickness categories;(4)forecast for evolving the model;(5)resampling for updating model uncertainties.Several experiments were conducted to examine its results and impacts.Compared with the control experiment,the continuous assimilation experiments(CTNs)indicate assimilations improve model SICs and SITs persistently and generate realistic initials.Assimilating SIC+SIT data better corrects overestimated model SITs spatially than when only assimilating SIC data.The continuous assimilation restart experiments indicate the initials from the CTNs correct the overestimated marginal SICs and overall SITs remarkably well,as well as the cold biases in the oceanic and atmospheric models.The initials with SIC+SIT assimilated show more reasonable spatial improvements.Nevertheless,the SICs in the central Arctic undergo abnormal summer reductions,which is probably because overestimated SITs are reduced in the initials but the strong seasonal cycle(summer melting)biases are unchanged.Therefore,since systematic biases are complicated in a coupled system,for FGOALS-f3-L to make better ice predictions,oceanic and atmospheric assimilations are expected required.展开更多
A two-dimensional energy balance climate model has been built to investigate the climate on Mars.The model takes into account the balance among solar radiation,longwave radiation,and energy transmission and can be sol...A two-dimensional energy balance climate model has been built to investigate the climate on Mars.The model takes into account the balance among solar radiation,longwave radiation,and energy transmission and can be solved analytically by Legendre polynomials.With the parameters for thermal diffusion and radiation processes being properly specified,the model can simulate a reasonable surface atmospheric temperature distribution but not a very perfect vertical atmospheric temperature distribution compared with numerical results,such as those from the Mars Climate Database.With varying solar radiation in a Martian year,the model can simulate the seasonal variation of the air temperature on Mars.With increasing dust content,the Martian atmosphere gradually warms.However,the warming is insignificant in the cold and warm scenarios,in which the dust mixing ratio varies moderately,whereas the warming is significant in the storm scenario,in which the dust mixing ratio increases dramatically.With an increasing albedo value of either the polar cap or the non-ice region,Mars gradually cools.The mean surface atmospheric temperature decreases moderately with an increasing polar ice albedo,whereas it increases dramatically with an increasing non-ice albedo.This increase occurs because the planetary albedo of the ice regions is smaller than that of the non-ice region.展开更多
Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of ...Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of physics in climate science has occasionally been overlooked.Our perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”scenario.Scrutinizing controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical constraints.Furthermore,we provide illustrative examples to guide future assessments and constraints for AI models.Regarding AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online schemes.Additionally,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)principles.Through a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal.展开更多
In 1995, the Intergovernmental Panel on Climate Change (IPCC) released a thermodynamic model based on the Greenhouse Effect, aiming to forecast global temperatures. This study delves into the intricacies of that model...In 1995, the Intergovernmental Panel on Climate Change (IPCC) released a thermodynamic model based on the Greenhouse Effect, aiming to forecast global temperatures. This study delves into the intricacies of that model. Some interesting observations are revealed. The IPCC model equated average temperatures with average energy fluxes, which can cause significant errors. The model assumed that all energy fluxes remained constant, and the Earth emitted infrared radiation as if it were a blackbody. Neither of those conditions exists. The IPCC’s definition of Climate Change only includes events caused by human actions, excluding most causes. Satellite data aimed at the tops of clouds may have inferred a high Greenhouse Gas absorption flux. The model showed more energy coming from the atmosphere than absorbed from the sun, which may have caused a violation of the First and Second Laws of Thermodynamics. There were unexpectedly large gaps in the satellite data that aligned with various absorption bands of Greenhouse Gases, possibly caused by photon scattering associated with re-emissions. Based on science, we developed a cloud-based climate model that complied with the Radiation Laws and the First and Second Laws of Thermodynamics. The Cloud Model showed that 81.3% of the outgoing reflected and infrared radiation was applicable to the clouds and water vapor. In comparison, the involvement of CO<sub>2</sub> was only 0.04%, making it too minuscule to measure reliably.展开更多
This study investigates the impacts of climate change on temperature and precipitation patterns across four governorates in southern Iraq—Basrah,Thi Qar,Al Muthanna,and Messan—using an inte-grated modeling framework...This study investigates the impacts of climate change on temperature and precipitation patterns across four governorates in southern Iraq—Basrah,Thi Qar,Al Muthanna,and Messan—using an inte-grated modeling framework that combines the Long Ashton Research Station Weather Generator(LARS-WG)with three CMIP5-based Global Climate Models(Hadley Centre Global Environmental Model version 2-Earth System(HadGEM2-ES)),European Community Earth-System Model(EC-Earth),and Model for Interdisciplinary Research on Climate version 5(MIROC5).Projections were generated for three future time periods(2021–2040,2041–2060,and 2061–2080)under two Representative Concentration Pathways(RCP4.5 and RCP8.5).By integrating high-resolution climate simulations with localized drought risk analy-sis,this study provides a detailed outlook on climate change trends in the region.The novelty of this research lies in its high-resolution,station-level analysis and its integration of localized statistical downscal-ing techniques to enhance the spatial applicability of coarse GCM outputs.Model calibration and validation 2 were performed using historical climate data(1990–2020),resulting in high accuracy across all stations(R=0.91–0.99;RMSE=0.19–2.78),thus reinforcing the robustness of the projections.Results indicate a significant rise in average annual maximum and minimum temperatures,with increases ranging from 0.88°C to 3.68°C by the end of the century,particularly under the RCP8.5 scenario.Precipitation patterns exhibit pronounced interannual variability,with the highest predicted increases reaching up to 19.26 mm per season,depending on the model and location.These shifts suggest heightened vulnerability to drought and water scarcity,particularly in already arid regions such as Muthanna and Thi Qar.The findings under-score the urgent need for adaptive strategies in water resource management and agricultural planning,providing decision-makers with region-specific climate insights critical for sustainable development under changing climate conditions.展开更多
As the impact of climate change intensifies,climate migration(climate change-induced migration)has become a pressing global issue that requires effective adaptation strategies to lessen its effects.Therefore,this stud...As the impact of climate change intensifies,climate migration(climate change-induced migration)has become a pressing global issue that requires effective adaptation strategies to lessen its effects.Therefore,this study delved into the complex relationship between climate change adaptation strategies and climate migration with food insecurity serving as a mediating factor.We collected sample data through face-to-face interviews in Khorramabad City,Iran from February to May in 2023.Using the Structural Equation Modeling(SEM),we explored how food insecurity influences the relationship between climate change adaptation strategies and climate migration.The findings showed that while climate change adaptation strategies can boost community resilience,their success is closely tied to levels of food insecurity.About 78.72%of the surveyed households experienced certain levels of food insecurity,increasing the risk of displacement due to climate-related disasters.Climate change adaptation strategies including economic strategies,irrigation management strategies,organic-oriented strategies,sustainable development-oriented strategies,and crop variety management strategies played a significant role in reducing climate migration.Moreover,we found that climate change adaptation strategies not only impact food security,but also shape migration decisions.This research underscores the importance of an integrated approach that links climate change adaptation strategies,climate migration,and food insecurity.This study emphasizes the importance of food security for formulating sustainable adaptation strategies.展开更多
Long-term droughts,temperature rise,and extreme weather events cause changes in runoff,evaporation,and transpiration in basins.These changes are more severe in arid and semi-arid regions.Since 2007,the discharge of ba...Long-term droughts,temperature rise,and extreme weather events cause changes in runoff,evaporation,and transpiration in basins.These changes are more severe in arid and semi-arid regions.Since 2007,the discharge of baseflow of the Zagros Mountain has decreased and made the supply of agricultural,industrial,and drinking water a big challenge.In this investigation,utilizing data from weather stations,the output of CORDEX,and the WetSpass model,the impact of climate change on river discharge in the Great Karun Basin(GKB)was examined.The temperature and precipitation projections for the period 2019-2040 were analyzed using the Coupled Model Intercomparison Project Phase Six(CMIP6)under scenarios SSP2-4.5 and SSP5-8.5.The findings reveal that the minimum and maximum temperatures are expected to increase by 0.2℃ to 5.1℃ and 0.1℃ to 3.6℃,respectively.Annual precipitation will decrease between 1.3%and 16.7%in scenario SSP2-4.5 and 23.4%in scenario SSP5-8.5.The results of the WetSpass Model for predicting future scenarios indicate a decrease in direct flow(5%),total discharge(27%),and interception(15%).As evapotranspiration will increase by 15%due to climate change,it will be more difficult to predict the water resources’volume of the Karoun Basin for the next decades.Adapting to climate change is the appropriate solution to solve this problem.Changes in temperature and precipitation in these areas pose major challenges to water resources.展开更多
The 19th Workshop on Antarctic Meteorology and Climate(WAMC)and the 8th Year of Polar Prediction in the Southern Hemisphere(YOPP-SH)meeting were held in June 2024 at the Byrd Polar and Climate Research Center,The Ohio...The 19th Workshop on Antarctic Meteorology and Climate(WAMC)and the 8th Year of Polar Prediction in the Southern Hemisphere(YOPP-SH)meeting were held in June 2024 at the Byrd Polar and Climate Research Center,The Ohio State University,Columbus,Ohio.These hybrid events convened 79 participants from 15 nations to foster international collaboration on Antarctic meteorology,climate research,and forecasting.The WAMC featured presentations on automatic weather stations,numerical weather prediction,Antarctic sea ice dynamics,and extreme weather events.The YOPP-SH meeting emphasized the positive impacts of enhanced observations during the 2022 Winter Special Observing Period(SOP)on forecast accuracy and addressed the transition toward the Polar Coupled Analysis and Prediction for Services(PCAPS)initiative.The outcomes reflect significant advancements in polar meteorological research and underscore the importance of sustained collaborative efforts,including improved observational networks and advanced modeling systems,to address the unique challenges of Antarctic meteorology.Future workshops will continue to support and expand upon these critical themes.展开更多
Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives ...Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives of billions who depend on or are affected by monsoons, as it is essential for the water cycle, food security, ecology, disaster prevention, and the economy of monsoon regions. Given the extensive literature on Asian monsoon climate prediction, we limit our focus to reviewing the seasonal prediction and predictability of the Asian Summer Monsoon (ASM). However, much of this review is also relevant to monsoon predictions in other seasons and regions. Over the past two decades, considerable progress has been made in the seasonal forecasting of the ASM, driven by an enhanced understanding of the sources of predictability and the dynamics of seasonal variability, along with advanced development in sophisticated models and technologies. This review centers on advances in understanding the physical foundation for monsoon climate prediction (section 2), significant findings and insights into the primary and regional sources of predictability arising from feedback processes among various climate components (sections 3 and 4), the effects of global warming and external forcings on predictability (section 5), developments in seasonal prediction models and techniques (section 6), the challenges and limitations of monsoon climate prediction (section 7), and emerging research trends with suggestions for future directions (section 8). We hope this review will stimulate creative activities to enhance monsoon climate prediction.展开更多
Medicinal plant diversity(MPD)is an indispensable part of global plant diversity,serving as the foundation for human survival by offering remedies and preventive measures against diseases.However,factors such as overe...Medicinal plant diversity(MPD)is an indispensable part of global plant diversity,serving as the foundation for human survival by offering remedies and preventive measures against diseases.However,factors such as overexploitation,competition from invasive alien species,and climate change,threaten the habitats of medicinal plants,necessitating a comprehensive understanding of their spatial distribution and suitable habitats.We leveraged a decade of field survey data on medicinal plant distribution in the Yinshan Mountains,combined with spatial analysis,species distribution modeling,and the Carnegie Ames Stanford Approach(CASA)to explore the MPD spatial distribution and suitable habitats.Spatial analysis revealed that the central and eastern parts of Yinshan Mountains were the primary MPD hotspots,with no cold spots evident at various spatial scales.As the spatial scale decreased,previous non-significant regions transformed into hotspots,with instances where large-scale hotspots became insignificant.These findings offer valuable guidance for safeguarding and nurturing MPD across diverse spatial scales.In future climate change scenarios within the shared socioeconomic pathways(SSP),the habitat suitability for MPD in the Yinshan Mountains predominantly remains concentrated in the central and eastern regions.Notably,areas with high net primary productivity(NPP)values and abundant vegetation coverage align closely with MPD habitat suitability areas,potentially contributing to the region's rich MPD.展开更多
Landslides pose a significant threat to both human society and environmental sustainability,yet,their spatiotemporal evolution and impacts on global scales in the context of a warming climate remain poorly understood....Landslides pose a significant threat to both human society and environmental sustainability,yet,their spatiotemporal evolution and impacts on global scales in the context of a warming climate remain poorly understood.In this study,we projected global landslide susceptibility under four shared socioeconomic pathways(SSPs)from 2021 to 2100,utilizing multiple machine learning models based on precipitation data from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs)and static metrics.Our results indicate an overall upward trend in global landslide susceptibility under the SSPs compared to the baseline period(2001–2020),with the most significant increase of about 1%in the very far future(2081–2100)under the high emissions scenario(SSP5-8.5).Currently,approximately 13%of the world’s land area is at very high risk of landslide,mainly in the Cordillera of the Americas and the Andes in South America,the Alps in Europe,the Ethiopian Highlands in Africa,the Himalayas in Asia,and the countries of East and South-East Asia.Notably,India is the country most adversely affected by climate change,particularly during 2081–2100 under SSP3-7.0,with approximately 590 million people—23 times the global average—living in areas categorized as having very high susceptibility.展开更多
Understanding the impacts of climate change on the future growth of tree species is particularly important for conserving endemic species with limited geographic distributions,such as Serbian spruce(Picea omorika(Panc...Understanding the impacts of climate change on the future growth of tree species is particularly important for conserving endemic species with limited geographic distributions,such as Serbian spruce(Picea omorika(Pancic)Purk.).This study describes an approach to assessing the effects of future climate conditions on the growth and the implications for future management to conserve this endangered species on the IUCN Red List.To investigate the climate-growth relationship,age structure and diameter growth trends,we have sampled 231 trees across 11 locations at National Park"Tara"in western Serbia.The existence of heterogeneous age structures suggests that Serbian spruce poses considerable potential for continual regeneration in stands with open canopy.Conducted dendroclimatological analysis exhibits exceptional coherence in growth patterns within populations(Rxy 0.67–0.78),allowing the established climate-sensitive mixed-effect model to achieve conditional R^(c)^(2)=0.683.It is revealed that the radial increment of Serbian spruce is dominantly regulated by water deficit in the summer season.The rainfall amount during the spring is another meaningful climatic factor for growth trends,while minimal winter temperatures and previous autumn water balance show varying influences.Finally,the growth projections under climate change scenarios RCP4.5 and RCP8.5 foreseen reductions of up to one-third and almost half from the historical mean growth rate.The given estimations should be seen as a critical warning signal calling for immediate conversion from passive to active protection to preserve this unique species.展开更多
Conversion of dryland to paddy fields(CDPF)is an effective way to transition from rain-fed to irrigated agricul ture,helping to mitigate the effects of climate change on agriculture and increase yields to meet growing...Conversion of dryland to paddy fields(CDPF)is an effective way to transition from rain-fed to irrigated agricul ture,helping to mitigate the effects of climate change on agriculture and increase yields to meet growing food demand.However,the suitability of CDPF is spatio-temporally dynamic but has often been neglected in previous studies.To fill this knowledge gap,this research developed a novel method for quantifying the suitability of CDPF,based on the MaxEnt model for application in Northeast China.We explored the spatiotemporal characteristics of the suitability of CDPF under the baseline scenario(2010-2020),and future projections(2030-2090)coupled with climate change and socioeconomic development scenarios(SSP126,SSP245,and SSP585),and revealed the driving factors behind it.Based on this,we identified potential priority areas for future CDPF implementation.The results show that the suitability of CDPF projects implemented in the past ten years is relatively high.Com pared with the baseline scenario,the suitability of CDPF under the future scenarios will decline overall,with the lightest decrease in the RCP585 and the most severe decrease in the RCP245.The key drivers affecting the suitability of CDPF are elevation,slope,population count,total nitrogen,soil organic carbon content,and precip itation seasonality.The potential priority areas for the future CDPF range from 6,284.61 km^(2)to 37,006.02 km^(2).These findings demonstrate the challenges of CDPF in adapting to climate change and food security,and provide insights for food-producing regions around the world facing climate crises.展开更多
Understanding how environmental adaptation varies among families within a species is critical to adapt forestry activities such as management and breeding to possible future climate change.The present study examined h...Understanding how environmental adaptation varies among families within a species is critical to adapt forestry activities such as management and breeding to possible future climate change.The present study examined home-site advantage and local advantage in growth and basic density of wood in 36 families of Chamaecyparis obtuse(Siebold et Zucc.)Endl.,reciprocally planted at two progeny test sites with differing climatic conditions in Japan.A significant home-site advantage for growth was detected between the lowland and mountainous regions within the Kanto breeding region.In addition,the effects of climate differentials between the selection site of mating parents and the progeny test site on growth and basic density were inves-tigated.As a result,temperature was identified as the most significant climatic factor attributed to local adaptation for growth traits.Elongation and radial growth were adversely influenced when the progeny test site temperature exceeded the provenance temperature by more than 2°C.Therefore,it is crucial to account for temperature differences between the provenance and the planting site to adapt afforestation and forest tree breeding to climate change in the future.展开更多
Comprehensive phylogeographic insights require the integration of evidence across diverse taxa,ecosystems,and geographical regions.However,our understanding of the arid biota of the vast Asian drylands remains limited...Comprehensive phylogeographic insights require the integration of evidence across diverse taxa,ecosystems,and geographical regions.However,our understanding of the arid biota of the vast Asian drylands remains limited.Accordingly,this study combined phylogeographic analyses with ecological niche modeling to investigate patterns of diversification and demography of the Central Asian racerunner(Eremias vermiculata),a widespread lizard inhabiting arid eastern-Central Asia(AECA).Mitochondrial DNA(mtDNA)sequences were obtained from 876 individuals across 113 localities,while three nuclear genes-CGNL1,MAP1A,andβ-fibint7-were sequenced from 204,170,and 138 individuals,respectively.Analyses identified four distinct mtDNA lineages corresponding to specific geographic subregions within the AECA,reflecting the topographic and ecological heterogeneity of the region.The detection of mito-nuclear discordance indicated the presence of complex evolutionary dynamics.Divergence dating placed the initial lineage splits at approximately 1.18 million years ago,coinciding with major tectonic activity and climatic aridification that likely promoted allopatric divergence.In particular,lineage diversification within the Tarim Basin suggests that recent environmental shifts may have contributed to genetic divergence.Demographic reconstructions revealed signatures of population expansion or range shifts across all lineages during the Last Glacial Maximum,signifying the combined influence of the unique topography and climate dynamics of the AECA on diversification and demographic change.These results highlight the need for fine-scale genomic investigations to clarify the mechanisms underlying mito-nuclear discordance and local adaptation.Such efforts are essential for advancing understanding of how genetic diversity in dryland taxa responds to environmental change,providing insights into the evolutionary adaptability of species in dynamic landscapes.展开更多
基金supported by the Shihezi University High-Level Talents Research Startup Project(Project No.RCZK202521)the National Natural Science Foundation of China(Grant Nos.12271066,11871121,12171405)+1 种基金the Chongqing Natural Science Foundation Joint Fund for Innovation and Development Project(Project No.CSTB2024NSCQLZX0085)the Chongqing Normal University Foundation(Grant No.23XLB018).
文摘This paper investigates ruin,capital injection,and dividends for a two-dimensional risk model.The model posits that surplus levels of insurance companies are governed by a perturbed composite Poisson risk model.This model introduces a dependence between the two surplus levels,present in both the associated perturbations and the claims resulting from common shocks.Critical levels of capital injection and dividends are established for each of the two risks.The surplus levels are observed discretely at fixed intervals,guiding decisions on capital injection,dividends,and ruin at these junctures.This study employs a two-dimensional Fourier cosine series expansion method to approximate the finite time expected discounted operating cost until ruin.The ensuing approximation error is also quantified.The validity and accuracy of the method are corroborated through numerical examples.Furthermore,the research delves into the optimal capital allocation problem.
基金supported by the National Natural Science Foundation of China(Grant Nos.42150204 and 2288101)supported by the China National Postdoctoral Program for Innovative Talents(BX20230045)the China Postdoctoral Science Foundation(2023M730279)。
文摘A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and development of the NMI model and then emphasize that the NMI model represents a new tool for identifying the basic physics of how climate change influences mid-to-high latitude weather extremes.The building of the NMI model took place over three main periods.In the 1990s,a nonlinear Schr?dinger(NLS)equation model was presented to describe atmospheric blocking as a wave packet;however,it could not depict the lifetime(10-20 days)of atmospheric blocking.In the 2000s,we proposed an NMI model of atmospheric blocking in a uniform basic flow by making a scale-separation assumption and deriving an eddyforced NLS equation.This model succeeded in describing the life cycle of atmospheric blocking.In the 2020s,the NMI model was extended to include the impact of a changing climate mainly by altering the basic zonal winds and the magnitude of the meridional background potential vorticity gradient(PVy).Model results show that when PVy is smaller,blocking has a weaker dispersion and a stronger nonlinearity,so blocking can be more persistent and have a larger zonal scale and weaker eastward movement,thus favoring stronger weather extremes.However,when PVy is much smaller and below a critical threshold under much stronger winter Arctic warming of global warming,atmospheric blocking becomes locally less persistent and shows a much stronger westward movement,which acts to inhibit local cold extremes.Such a case does not happen in summer under global warming because PVy fails to fall below the critical threshold.Thus,our theory indicates that global warming can render summer-blocking anticyclones and mid-to-high latitude heatwaves more persistent,intense,and widespread.
基金This study was supported by the National Natural Science Foundation of China(Grant No.U2342228)the National Key Program for Developing Basic Sciences(Grant No.2020YFA0608902)+1 种基金the National Natural Science Foundation of China(Grant Nos.92358302,and 42242018)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0500303).
文摘In recent decades,large ensemble simulation(LENS)or super-large ensemble simulation(SLENS)experiments with climate models,including the simulation of both the historical and future climate,have been increasingly exploited in the fields of climate change,climate variability,climate projection,and beyond.This paper provides an overview of LENS in climate systems.It delves into its definition,initialization,significance,and scientific concerns.Additionally,its development history and relevant theories,methods,and primary fields of application are also reviewed.Conclusions obtained from single-model LENS can be more robust compared with those from ensemble simulations with smaller numbers of members.The interactions among model biases,forced responses,and internal variabilities,which serve as the added value in LENS,are highlighted.Finally,we put forward the future trajectory of LENS with climate or Earth system models(ESMs).Super-large ensemble simulation,high-resolution LENS,LENS employing ESMs,and combining LENS with artificial intelligence,will greatly promote the study of climate and related applications.
基金supported by National Natural Science Foundation of China(72288101,72361137002,and 72101018)the Dutch Research Council(NWO Grant 482.22.01).
文摘Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subsequent impact on urban structure.Considering the varying travel costs associated with electric and fuel vehicles,we analyze the dynamic choices of households concerning house locations and vehicle types in a two-dimensional monocentric city.A spatial equilibrium is developed to model the interactions between urban density,vehicle age and vehicle type.An agent-based microeconomic residential choice model dynamically coupled with a house rent market is developed to analyze household choices of home locations and vehicle energy types,considering vehicle ages and competition for public charging piles.Key findings from our proposed models show that the proportion of electric vehicles(EVs)peaks at over 50%by the end of the first scrappage period,accompanied by more than a 40%increase in commuting distance and time compared to the scenario with only fuel vehicles.Simulation experiments on a theoretical grid indicate that heterogeneity-induced residential segregation can lead to urban sprawl and congestion.Furthermore,households with EVs tend to be located farther from the city center,and an increase in EV ownership contributes to urban expansion.Our study provides insights into how individuals adapt to EV transitions and the resulting impacts on home locations and land use changes.It offers a novel perspective on the dynamic interactions between EV adoption and urban development.
基金the National Natural Science Foundation of China(NSFC 31761143002,NSFC 3207178)China Postdoctoral Science Foundation(2022M710405)the National Forest and Grassland Genetic Recourse(No.2005DKA21003).
文摘The influence of global climate change on endangered species is of growing concern, especially for rosewood species that are in urgent need of protection and restoration. Ecological niche models are commonly used to evaluate probable species’ distribution under climate change and contribute to decision-making to define efficient management strategies. A model was developed to forecast which habitat was most likely appropriate for the Dalbergia odorifera. We screened the main climatic variables that describe the current geographic distribution of the species based on maximum entropy modelling (Maxent). We subsequently assessed its potential future distribution under moderate (RCP2.6) and severe (RCP8.5) climate change scenarios for the years 2050 and 2070. The precipitation ranges of the wettest month and the warmest quarter are the primary limiting factors for the current distribution of D. odorifera among the climatic predictors. Climate change will be expected to have beneficial effects on the distribution range of D. odorifera. In conclusion, the main limits for the distribution of D. odorifera are determined by the level of precipitation and human activities. The results of this study indicate that the coasts of southern China and Chongqing will play a key role in the protection and restoration of D. odorifera in the future.
基金jointly funded by the National Natural Science Foundation of China(NSFC)[grant number 42130608]the China Postdoctoral Science Foundation[grant number 2024M753169]。
文摘Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this study,a Localized Error Subspace Transform Kalman Filter is employed in a coupled climate system model(the Flexible Global Ocean–Atmosphere–Land System Model,version f3-L(FGOALS-f3-L))to assimilate sea-ice concentration(SIC)and sea-ice thickness(SIT)data for melting-season ice predictions.The scheme is applied through the following steps:(1)initialization for generating initial ensembles;(2)analysis for assimilating observed data;(3)adoption for dividing ice states into five thickness categories;(4)forecast for evolving the model;(5)resampling for updating model uncertainties.Several experiments were conducted to examine its results and impacts.Compared with the control experiment,the continuous assimilation experiments(CTNs)indicate assimilations improve model SICs and SITs persistently and generate realistic initials.Assimilating SIC+SIT data better corrects overestimated model SITs spatially than when only assimilating SIC data.The continuous assimilation restart experiments indicate the initials from the CTNs correct the overestimated marginal SICs and overall SITs remarkably well,as well as the cold biases in the oceanic and atmospheric models.The initials with SIC+SIT assimilated show more reasonable spatial improvements.Nevertheless,the SICs in the central Arctic undergo abnormal summer reductions,which is probably because overestimated SITs are reduced in the initials but the strong seasonal cycle(summer melting)biases are unchanged.Therefore,since systematic biases are complicated in a coupled system,for FGOALS-f3-L to make better ice predictions,oceanic and atmospheric assimilations are expected required.
基金jointly funded by the National Natural Science Foundation of China (Grant 41505042)the National Program on Global Change and Air–Sea Interaction (Grant GASIIPOVAI-03)+1 种基金the National Basis Research Program of China (Grants 2015CB953601, 2014CB953903)the Fundamental Research Funds for the Central Universities
文摘A two-dimensional energy balance climate model has been built to investigate the climate on Mars.The model takes into account the balance among solar radiation,longwave radiation,and energy transmission and can be solved analytically by Legendre polynomials.With the parameters for thermal diffusion and radiation processes being properly specified,the model can simulate a reasonable surface atmospheric temperature distribution but not a very perfect vertical atmospheric temperature distribution compared with numerical results,such as those from the Mars Climate Database.With varying solar radiation in a Martian year,the model can simulate the seasonal variation of the air temperature on Mars.With increasing dust content,the Martian atmosphere gradually warms.However,the warming is insignificant in the cold and warm scenarios,in which the dust mixing ratio varies moderately,whereas the warming is significant in the storm scenario,in which the dust mixing ratio increases dramatically.With an increasing albedo value of either the polar cap or the non-ice region,Mars gradually cools.The mean surface atmospheric temperature decreases moderately with an increasing polar ice albedo,whereas it increases dramatically with an increasing non-ice albedo.This increase occurs because the planetary albedo of the ice regions is smaller than that of the non-ice region.
基金supported by the National Natural Science Foundation of China(Grant Nos.42141019 and 42261144687)and STEP(Grant No.2019QZKK0102)supported by the Korea Environmental Industry&Technology Institute(KEITI)through the“Project for developing an observation-based GHG emissions geospatial information map”,funded by the Korea Ministry of Environment(MOE)(Grant No.RS-2023-00232066).
文摘Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of physics in climate science has occasionally been overlooked.Our perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”scenario.Scrutinizing controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical constraints.Furthermore,we provide illustrative examples to guide future assessments and constraints for AI models.Regarding AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online schemes.Additionally,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)principles.Through a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal.
文摘In 1995, the Intergovernmental Panel on Climate Change (IPCC) released a thermodynamic model based on the Greenhouse Effect, aiming to forecast global temperatures. This study delves into the intricacies of that model. Some interesting observations are revealed. The IPCC model equated average temperatures with average energy fluxes, which can cause significant errors. The model assumed that all energy fluxes remained constant, and the Earth emitted infrared radiation as if it were a blackbody. Neither of those conditions exists. The IPCC’s definition of Climate Change only includes events caused by human actions, excluding most causes. Satellite data aimed at the tops of clouds may have inferred a high Greenhouse Gas absorption flux. The model showed more energy coming from the atmosphere than absorbed from the sun, which may have caused a violation of the First and Second Laws of Thermodynamics. There were unexpectedly large gaps in the satellite data that aligned with various absorption bands of Greenhouse Gases, possibly caused by photon scattering associated with re-emissions. Based on science, we developed a cloud-based climate model that complied with the Radiation Laws and the First and Second Laws of Thermodynamics. The Cloud Model showed that 81.3% of the outgoing reflected and infrared radiation was applicable to the clouds and water vapor. In comparison, the involvement of CO<sub>2</sub> was only 0.04%, making it too minuscule to measure reliably.
文摘This study investigates the impacts of climate change on temperature and precipitation patterns across four governorates in southern Iraq—Basrah,Thi Qar,Al Muthanna,and Messan—using an inte-grated modeling framework that combines the Long Ashton Research Station Weather Generator(LARS-WG)with three CMIP5-based Global Climate Models(Hadley Centre Global Environmental Model version 2-Earth System(HadGEM2-ES)),European Community Earth-System Model(EC-Earth),and Model for Interdisciplinary Research on Climate version 5(MIROC5).Projections were generated for three future time periods(2021–2040,2041–2060,and 2061–2080)under two Representative Concentration Pathways(RCP4.5 and RCP8.5).By integrating high-resolution climate simulations with localized drought risk analy-sis,this study provides a detailed outlook on climate change trends in the region.The novelty of this research lies in its high-resolution,station-level analysis and its integration of localized statistical downscal-ing techniques to enhance the spatial applicability of coarse GCM outputs.Model calibration and validation 2 were performed using historical climate data(1990–2020),resulting in high accuracy across all stations(R=0.91–0.99;RMSE=0.19–2.78),thus reinforcing the robustness of the projections.Results indicate a significant rise in average annual maximum and minimum temperatures,with increases ranging from 0.88°C to 3.68°C by the end of the century,particularly under the RCP8.5 scenario.Precipitation patterns exhibit pronounced interannual variability,with the highest predicted increases reaching up to 19.26 mm per season,depending on the model and location.These shifts suggest heightened vulnerability to drought and water scarcity,particularly in already arid regions such as Muthanna and Thi Qar.The findings under-score the urgent need for adaptive strategies in water resource management and agricultural planning,providing decision-makers with region-specific climate insights critical for sustainable development under changing climate conditions.
基金support provided by the Department of Agricultural Economics and Rural Development,Faculty of Agriculture,Lorestan University,Iran.
文摘As the impact of climate change intensifies,climate migration(climate change-induced migration)has become a pressing global issue that requires effective adaptation strategies to lessen its effects.Therefore,this study delved into the complex relationship between climate change adaptation strategies and climate migration with food insecurity serving as a mediating factor.We collected sample data through face-to-face interviews in Khorramabad City,Iran from February to May in 2023.Using the Structural Equation Modeling(SEM),we explored how food insecurity influences the relationship between climate change adaptation strategies and climate migration.The findings showed that while climate change adaptation strategies can boost community resilience,their success is closely tied to levels of food insecurity.About 78.72%of the surveyed households experienced certain levels of food insecurity,increasing the risk of displacement due to climate-related disasters.Climate change adaptation strategies including economic strategies,irrigation management strategies,organic-oriented strategies,sustainable development-oriented strategies,and crop variety management strategies played a significant role in reducing climate migration.Moreover,we found that climate change adaptation strategies not only impact food security,but also shape migration decisions.This research underscores the importance of an integrated approach that links climate change adaptation strategies,climate migration,and food insecurity.This study emphasizes the importance of food security for formulating sustainable adaptation strategies.
基金Iran Water Resources Management Company (IWRMC)the Vice Chancellor for Research and Technology at the University of Isfahan
文摘Long-term droughts,temperature rise,and extreme weather events cause changes in runoff,evaporation,and transpiration in basins.These changes are more severe in arid and semi-arid regions.Since 2007,the discharge of baseflow of the Zagros Mountain has decreased and made the supply of agricultural,industrial,and drinking water a big challenge.In this investigation,utilizing data from weather stations,the output of CORDEX,and the WetSpass model,the impact of climate change on river discharge in the Great Karun Basin(GKB)was examined.The temperature and precipitation projections for the period 2019-2040 were analyzed using the Coupled Model Intercomparison Project Phase Six(CMIP6)under scenarios SSP2-4.5 and SSP5-8.5.The findings reveal that the minimum and maximum temperatures are expected to increase by 0.2℃ to 5.1℃ and 0.1℃ to 3.6℃,respectively.Annual precipitation will decrease between 1.3%and 16.7%in scenario SSP2-4.5 and 23.4%in scenario SSP5-8.5.The results of the WetSpass Model for predicting future scenarios indicate a decrease in direct flow(5%),total discharge(27%),and interception(15%).As evapotranspiration will increase by 15%due to climate change,it will be more difficult to predict the water resources’volume of the Karoun Basin for the next decades.Adapting to climate change is the appropriate solution to solve this problem.Changes in temperature and precipitation in these areas pose major challenges to water resources.
基金support from the Office of Polar Programs of the National Science Foundation(Grant Nos.2205398,2233182,1951720,1951603,2301362).
文摘The 19th Workshop on Antarctic Meteorology and Climate(WAMC)and the 8th Year of Polar Prediction in the Southern Hemisphere(YOPP-SH)meeting were held in June 2024 at the Byrd Polar and Climate Research Center,The Ohio State University,Columbus,Ohio.These hybrid events convened 79 participants from 15 nations to foster international collaboration on Antarctic meteorology,climate research,and forecasting.The WAMC featured presentations on automatic weather stations,numerical weather prediction,Antarctic sea ice dynamics,and extreme weather events.The YOPP-SH meeting emphasized the positive impacts of enhanced observations during the 2022 Winter Special Observing Period(SOP)on forecast accuracy and addressed the transition toward the Polar Coupled Analysis and Prediction for Services(PCAPS)initiative.The outcomes reflect significant advancements in polar meteorological research and underscore the importance of sustained collaborative efforts,including improved observational networks and advanced modeling systems,to address the unique challenges of Antarctic meteorology.Future workshops will continue to support and expand upon these critical themes.
基金supported by the National Natural Science Foundation of China(Grant No.U2342208)support from NSF/Climate Dynamics Award#2025057。
文摘Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives of billions who depend on or are affected by monsoons, as it is essential for the water cycle, food security, ecology, disaster prevention, and the economy of monsoon regions. Given the extensive literature on Asian monsoon climate prediction, we limit our focus to reviewing the seasonal prediction and predictability of the Asian Summer Monsoon (ASM). However, much of this review is also relevant to monsoon predictions in other seasons and regions. Over the past two decades, considerable progress has been made in the seasonal forecasting of the ASM, driven by an enhanced understanding of the sources of predictability and the dynamics of seasonal variability, along with advanced development in sophisticated models and technologies. This review centers on advances in understanding the physical foundation for monsoon climate prediction (section 2), significant findings and insights into the primary and regional sources of predictability arising from feedback processes among various climate components (sections 3 and 4), the effects of global warming and external forcings on predictability (section 5), developments in seasonal prediction models and techniques (section 6), the challenges and limitations of monsoon climate prediction (section 7), and emerging research trends with suggestions for future directions (section 8). We hope this review will stimulate creative activities to enhance monsoon climate prediction.
基金The National Key Research and Development Program of China,No.2021YFE0190100Inner Mongolia Autonomous Region Mongolian Medicine Standardization Project,No.2023-[MB023]The Earmarked Fund for CARS,No.CARS-21。
文摘Medicinal plant diversity(MPD)is an indispensable part of global plant diversity,serving as the foundation for human survival by offering remedies and preventive measures against diseases.However,factors such as overexploitation,competition from invasive alien species,and climate change,threaten the habitats of medicinal plants,necessitating a comprehensive understanding of their spatial distribution and suitable habitats.We leveraged a decade of field survey data on medicinal plant distribution in the Yinshan Mountains,combined with spatial analysis,species distribution modeling,and the Carnegie Ames Stanford Approach(CASA)to explore the MPD spatial distribution and suitable habitats.Spatial analysis revealed that the central and eastern parts of Yinshan Mountains were the primary MPD hotspots,with no cold spots evident at various spatial scales.As the spatial scale decreased,previous non-significant regions transformed into hotspots,with instances where large-scale hotspots became insignificant.These findings offer valuable guidance for safeguarding and nurturing MPD across diverse spatial scales.In future climate change scenarios within the shared socioeconomic pathways(SSP),the habitat suitability for MPD in the Yinshan Mountains predominantly remains concentrated in the central and eastern regions.Notably,areas with high net primary productivity(NPP)values and abundant vegetation coverage align closely with MPD habitat suitability areas,potentially contributing to the region's rich MPD.
基金supported by the project of National Natural Science Foundation of China(Grant No.42371203 and U21A2032)the project of Sichuan Provincial Science and Technology Department Program Funding(Grant No.2025YFHZ0010)the project of the Science and Technology Program of Aba City(Grant NO.R24YYJSYJ0001).
文摘Landslides pose a significant threat to both human society and environmental sustainability,yet,their spatiotemporal evolution and impacts on global scales in the context of a warming climate remain poorly understood.In this study,we projected global landslide susceptibility under four shared socioeconomic pathways(SSPs)from 2021 to 2100,utilizing multiple machine learning models based on precipitation data from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs)and static metrics.Our results indicate an overall upward trend in global landslide susceptibility under the SSPs compared to the baseline period(2001–2020),with the most significant increase of about 1%in the very far future(2081–2100)under the high emissions scenario(SSP5-8.5).Currently,approximately 13%of the world’s land area is at very high risk of landslide,mainly in the Cordillera of the Americas and the Andes in South America,the Alps in Europe,the Ethiopian Highlands in Africa,the Himalayas in Asia,and the countries of East and South-East Asia.Notably,India is the country most adversely affected by climate change,particularly during 2081–2100 under SSP3-7.0,with approximately 590 million people—23 times the global average—living in areas categorized as having very high susceptibility.
基金supported by the perennial project activities financed by National Park“Tara”(grants no.1159&1344)The research engagement of M.K.and B.S.was supported by the Ministry of Education,Science and Technological Development of the Republic of Serbia within the framework of the program technological development(grant no.200169)+1 种基金The work of M.K.was also supported by the Science Fond of the Republic of Serbia,grant no.6686EO and in situ based information framework to support generating Carbon Credits in forestry-ForestCO2。
文摘Understanding the impacts of climate change on the future growth of tree species is particularly important for conserving endemic species with limited geographic distributions,such as Serbian spruce(Picea omorika(Pancic)Purk.).This study describes an approach to assessing the effects of future climate conditions on the growth and the implications for future management to conserve this endangered species on the IUCN Red List.To investigate the climate-growth relationship,age structure and diameter growth trends,we have sampled 231 trees across 11 locations at National Park"Tara"in western Serbia.The existence of heterogeneous age structures suggests that Serbian spruce poses considerable potential for continual regeneration in stands with open canopy.Conducted dendroclimatological analysis exhibits exceptional coherence in growth patterns within populations(Rxy 0.67–0.78),allowing the established climate-sensitive mixed-effect model to achieve conditional R^(c)^(2)=0.683.It is revealed that the radial increment of Serbian spruce is dominantly regulated by water deficit in the summer season.The rainfall amount during the spring is another meaningful climatic factor for growth trends,while minimal winter temperatures and previous autumn water balance show varying influences.Finally,the growth projections under climate change scenarios RCP4.5 and RCP8.5 foreseen reductions of up to one-third and almost half from the historical mean growth rate.The given estimations should be seen as a critical warning signal calling for immediate conversion from passive to active protection to preserve this unique species.
基金supported by the Ministry of Education of Human-ities and Social Science project,China(Grant No.21YJA630121)the National Key Technology R&D Program of Ministry of Science and Technology of China(Grant No.2023YFD1500103)+2 种基金the Tsinghua Rural Studies PhD Scholarship(Grant No.202323)2023 Gradu-ate Innovation Fund Project of China University of Geosciences,Beijing(Grant No.ZD2023YC043)National Social Science Fund of China(Grants No.19ZDA096 and 20&ZD090)。
文摘Conversion of dryland to paddy fields(CDPF)is an effective way to transition from rain-fed to irrigated agricul ture,helping to mitigate the effects of climate change on agriculture and increase yields to meet growing food demand.However,the suitability of CDPF is spatio-temporally dynamic but has often been neglected in previous studies.To fill this knowledge gap,this research developed a novel method for quantifying the suitability of CDPF,based on the MaxEnt model for application in Northeast China.We explored the spatiotemporal characteristics of the suitability of CDPF under the baseline scenario(2010-2020),and future projections(2030-2090)coupled with climate change and socioeconomic development scenarios(SSP126,SSP245,and SSP585),and revealed the driving factors behind it.Based on this,we identified potential priority areas for future CDPF implementation.The results show that the suitability of CDPF projects implemented in the past ten years is relatively high.Com pared with the baseline scenario,the suitability of CDPF under the future scenarios will decline overall,with the lightest decrease in the RCP585 and the most severe decrease in the RCP245.The key drivers affecting the suitability of CDPF are elevation,slope,population count,total nitrogen,soil organic carbon content,and precip itation seasonality.The potential priority areas for the future CDPF range from 6,284.61 km^(2)to 37,006.02 km^(2).These findings demonstrate the challenges of CDPF in adapting to climate change and food security,and provide insights for food-producing regions around the world facing climate crises.
文摘Understanding how environmental adaptation varies among families within a species is critical to adapt forestry activities such as management and breeding to possible future climate change.The present study examined home-site advantage and local advantage in growth and basic density of wood in 36 families of Chamaecyparis obtuse(Siebold et Zucc.)Endl.,reciprocally planted at two progeny test sites with differing climatic conditions in Japan.A significant home-site advantage for growth was detected between the lowland and mountainous regions within the Kanto breeding region.In addition,the effects of climate differentials between the selection site of mating parents and the progeny test site on growth and basic density were inves-tigated.As a result,temperature was identified as the most significant climatic factor attributed to local adaptation for growth traits.Elongation and radial growth were adversely influenced when the progeny test site temperature exceeded the provenance temperature by more than 2°C.Therefore,it is crucial to account for temperature differences between the provenance and the planting site to adapt afforestation and forest tree breeding to climate change in the future.
基金supported by the Central Asia Drug Discovery and Development Centre of Chinese Academy of Sciences(180GJHZ2024036MI)National Natural Science Foundation of China(32070433,32470466,31672270,31872959)+2 种基金Third Xinjiang Scientific Expedition Program(2021xjkk0600)Special Exchange Program of the Chinese Academy of Sciencessponsored by the ANSO Scholarship for Young Talents
文摘Comprehensive phylogeographic insights require the integration of evidence across diverse taxa,ecosystems,and geographical regions.However,our understanding of the arid biota of the vast Asian drylands remains limited.Accordingly,this study combined phylogeographic analyses with ecological niche modeling to investigate patterns of diversification and demography of the Central Asian racerunner(Eremias vermiculata),a widespread lizard inhabiting arid eastern-Central Asia(AECA).Mitochondrial DNA(mtDNA)sequences were obtained from 876 individuals across 113 localities,while three nuclear genes-CGNL1,MAP1A,andβ-fibint7-were sequenced from 204,170,and 138 individuals,respectively.Analyses identified four distinct mtDNA lineages corresponding to specific geographic subregions within the AECA,reflecting the topographic and ecological heterogeneity of the region.The detection of mito-nuclear discordance indicated the presence of complex evolutionary dynamics.Divergence dating placed the initial lineage splits at approximately 1.18 million years ago,coinciding with major tectonic activity and climatic aridification that likely promoted allopatric divergence.In particular,lineage diversification within the Tarim Basin suggests that recent environmental shifts may have contributed to genetic divergence.Demographic reconstructions revealed signatures of population expansion or range shifts across all lineages during the Last Glacial Maximum,signifying the combined influence of the unique topography and climate dynamics of the AECA on diversification and demographic change.These results highlight the need for fine-scale genomic investigations to clarify the mechanisms underlying mito-nuclear discordance and local adaptation.Such efforts are essential for advancing understanding of how genetic diversity in dryland taxa responds to environmental change,providing insights into the evolutionary adaptability of species in dynamic landscapes.
