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
Climate change is altering vegetation phenology,differentially affecting food quality and availability for the gosling development(and therefore fitness)of migratory herbivores,especially those experiencing range cont...Climate change is altering vegetation phenology,differentially affecting food quality and availability for the gosling development(and therefore fitness)of migratory herbivores,especially those experiencing range contraction and fragmentation.By quantifying the climate-vegetation nexus for two waterbird species of contrasting conservation status,we assessed the differential implications of climate change in semi-arid landscapes for gosling development windows in different parts of their mid-latitude breeding ranges.We defined breeding ranges using telemetry data from 663 summering tracks of tagged Swan Geese(Anser cygnoides)and Greylag Geese(A.anser)breeding across the Mongolian Plateau.Within these areas,we systematically analyzed spatiotemporal variations in vegetation phenology based on MODIS NDVI datasets from 2000 to 2024 and their response to climate factors.Combining the above data,we demonstrated synchrony between goose breeding phenology and vegetation phenological indices:gosling hatching coincided with the start of growing season(SOS),autumn migration initiation with the end of growing season(EOS).We determined temporal and geographical variation in vegetation SOS,EOS and the length of growing season(LOS=EOS-SOS)as a proxy for gosling development windows across the Mongolian Plateau.Mean LOS was 107±13 days,generally sufficient for gosling development(c.113 days),but showed spatial heterogeneity,increasing in the west but shortening in the east of Mongolian Plateau.SOS was delayed with higher land surface temperature and lower precipitation/aridity in central/eastern Mongolian Plateau,but advanced in the west.Elevation of these three climatic factors delayed EOS across Mongolian Plateau.Climate warming and hydric stress may trigger synergistic SOS-delay and EOS-advance effects in the central and eastern Mongolian Plateau,increasing differential phenological mismatch risks to offspring fitness,thereby potentially affecting population growth rates and distributions.展开更多
Land degradation,coupled with climate change impacts,poses serious threats to global land health and human well-being.Participatory scenario planning(PSP)has become a key tool for exploring these interconnected challe...Land degradation,coupled with climate change impacts,poses serious threats to global land health and human well-being.Participatory scenario planning(PSP)has become a key tool for exploring these interconnected challenges;however,its progress and effectiveness remain underexplored.This study reviews 46 papers,using PRISMA guidelines,to investigate how PSP supports sustainable land management and climate resilience.We document how PSP applications have evolved from a biophysical focus to one addressing broader environmental,societal,and economic challenges.Disparities in how participants engage across PSP phases document the need for more equitable and meaningful participation.Clustering future scenarios reveals the complex interconnections among ecological,social,and economic factors underpinning land management and climate resilience,underscoring the need for inclusive and integrated strategies.From the emerging trends,we identify opportunities to advance PSP implementation,including early engagement of decision-makers,balanced representation and equitable power dynamics,meaningful participation,cross-disciplinary collaboration,integration of human-nature relationships,and regular revision of future pathways.Overall,our review highlights PSP’s potential to co-create inclusive,equitable scenarios and actionable pathways towards sustainable and resilient land use futures.展开更多
Precise forecasts of wildfire danger are crucial for proactive fuel management and emergency responses,yet they pose a challenge at the subseasonal scale due to limitations in prediction capabilities and a gap between...Precise forecasts of wildfire danger are crucial for proactive fuel management and emergency responses,yet they pose a challenge at the subseasonal scale due to limitations in prediction capabilities and a gap between forecast outputs and the needs of decision-makers.This study introduces an innovative hybrid modeling framework that integrates artificial intelligence(AI)with climate dynamic prediction systems to accurately forecast High Fire-Danger Days(HFDDs)for the following month.These HFDDs are derived from historical satellite fire data and the optimum fire danger index,with a particular focus on Southwest China as a case study.The AI module,based on the ResNet-18 neural network model,integrates observational and physically constrained analysis to establish links between HFDDs and optimal predictors of atmospheric circulation from both the concurrent and preceding months.Leveraging climate dynamical forecasting,this hybrid model provides more reliable deterministic predictions for monthly HFDDs than conventional methods that rely solely on terrestrial variables such as precipitation.More importantly,the integration of dynamical ensemble prediction enhances the model’s capability for skillful probabilistic predictions of HFDDs,facilitating the creation of customized fire danger outlooks and emergency action maps tailored to stakeholders’needs.The model’s added economic value was also evaluated,demonstrating its potential to improve decision-making in disaster management and bridge the“last-mile gap”in climate service delivery.This work contributes to the Seamless Prediction and Services for Sustainable Natural and Built Environment(SEPRESS)Program(2025–32),under the United Nations Educational Scientific and Cultural Organization(UNESCO)International Decade of Sciences for Sustainable Development(2024–33).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
Understanding how genetic variation within forest species influences growth responses under climate change is essential for improving the accuracy of forest models and guiding adaptive management strategies.This study...Understanding how genetic variation within forest species influences growth responses under climate change is essential for improving the accuracy of forest models and guiding adaptive management strategies.This study models the dynamics of Italian silver fir(Abies alba)forests under varying climate change scenarios using the forest gap model FORMIND.Focusing on three distinct silver fir provenances(Western Alps,Northern Apennines,and Southern Apennines),the study simulates forest growth in the Tuscan-Emilian Apennine National Park under different representative concentration pathways(RCPs).The individual-based model FORMIND was parameterized and validated with field data for each of the provenances,demonstrating its ability to accurately reproduce key forest metrics and dynamics.Our results reveal significant differences in expected growth patterns,productivity,metabolism,and carbon storage capacity among the silver fir provenances in pure and mixed stands.In the simulations,the Northern Apennines provenance showed higher biomass production(biomass>10%±1%)and carbon uptake(net primary productivity,NPP>8%±1%)at the end of the century compared to the Western Alps provenance in the pure provenance(PP)and no regeneration scenario.Conversely,the Southern Apennines provenance showed higher biomass(biomass>5%–10%)and NPP(>15%–18%)in mixed provenance(MP)and regeneration scenarios.These results show that genetic diversity strongly affects forest growth and resilience to environmental changes.Hence,it should be included as a predictor variable in forest models.The study also demonstrates the resilience of silver fir to climatic stressors,emphasizing its potential as a robust species in multiple forest contexts.The integration of forest provenance data into the FORMIND model represents a significant advancement in forest modelling,enabling more accurate and reliable predictions under climate change scenarios.The study's findings advocate for a greater understanding and consideration of genetic diversity in forest management and conservation strategies,in support of assisted migration strategies aiming to enhance the resilience of forest ecosystems in a changing climate.展开更多
Climate change poses significant risks to agriculture,particularly in East Asia,a major crop-producing region.This study evaluates the effectiveness of near-term climate predictions in forecasting agricultural thermal...Climate change poses significant risks to agriculture,particularly in East Asia,a major crop-producing region.This study evaluates the effectiveness of near-term climate predictions in forecasting agricultural thermal conditions in East Asia for up to five years.We compare temperature-based agroclimatic indicators from atmospheric reanalysis data with the firstyear prediction of the Decadal Prediction System version 4(DePreSys4),initialized annually from November 1960 to 2024.Our analysis reveals that first-year predictions accurately represent observed spatial climatological patterns,although trends in agroclimatic indicators based on daily maximum temperature are overestimated.High skill scores are observed in predicting the beginning of the growing season,frost-free days,agricultural hot days,and heat intensity in major cropping regions.However,the end of the growing season is less predictable due to longer lead times.Notably,five-year average predictions show higher skill than first-year predictions due to smoothed interannual variability.These improved climate predictions enable farmers and policymakers to make informed decisions about crop selection and agricultural infrastructure.展开更多
This study examined the role of green energy development in mitigating climate change and fostering sustainable development in Central Asia including Kazakhstan,Uzbekistan,Kyrgyzstan,Tajikistan,and Turkmenistan.The re...This study examined the role of green energy development in mitigating climate change and fostering sustainable development in Central Asia including Kazakhstan,Uzbekistan,Kyrgyzstan,Tajikistan,and Turkmenistan.The region has substantial untapped potential in solar energy,wind energy,hydropower energy,as well as biomass and bioenergy,positioning it strategically for renewable energy deployment.The result demonstrated that integrating renewable energy can reduce greenhouse gas emissions,improve air quality,enhance energy security,and support rural development.Case studies from Kazakhstan,Uzbekistan,Kyrgyzstan,and Tajikistan showed measurable environmental and economic benefits.However,the large-scale use of renewable energy still faces numerous barriers,including outdated infrastructure,fragmented regulatory frameworks,limited investment,and shortages of technical expertise.Overcoming these obstacles requires institutional reform,stronger regional cooperation,and increasing engagement from international financial institutions and private investors.Modernizing grids,deploying storage systems,and investing in education,research,and innovation are critical for building human capacity in renewable energy sector.Accelerating the renewable energy transition is essential for Central Asia to meet climate goals,enhance environmental resilience,and ensure long-term socioeconomic development through innovation,investment,and regional collaboration.展开更多
Giant kelp Macrocystis pyrifera,an important foundation species with great ecological and economic value,is threatened by climate change.To better understand the impact of climate warming on M.pyrifera,we investigated...Giant kelp Macrocystis pyrifera,an important foundation species with great ecological and economic value,is threatened by climate change.To better understand the impact of climate warming on M.pyrifera,we investigated its global distribution dynamics by an optimized species distribution model(SDM).Results showed that wave height,sea surface temperature,benthic temperature,and benthic phosphate concentration were key factors shaping the distribution of M.pyrifera.In addition to currently known distribution regions,the model revealed potential suitable habitats globally.Under future climate scenarios,the habitat suitability of M.pyrifera would decrease at low latitudes and increase at high latitudes,resulting in a poleward shift of suitable habitats.In the regions currently occupied by M.pyrifera,the high suitable habitats were predicted to shrink,which implies that the existing M.pyrifera would be adversely impacted.These results serve as references for the conservation and utilization of M.pyrifera resource.展开更多
Two international conferences in November 2025 jointly outlined a profound transformation of climate governance.The Committee on Trade and Environment(CTE)of the World Trade Organization(WTO)held a conference in Genev...Two international conferences in November 2025 jointly outlined a profound transformation of climate governance.The Committee on Trade and Environment(CTE)of the World Trade Organization(WTO)held a conference in Geneva,Switzerland,on November 4,where the topic of cooperation on trade-related carbon standards aroused heated discussions.The Leaders'Summit of the 30th Conference of the Parties(COP)to the UN Framework Convention on Climate Change(UNFCCC)was held in Belém,Brazil,on November 7.At the meeting,the Open Coalition on Compliance Carbon Markets was officially launched with the initial membership of 11 economies including Brazil,China,and the EU.As the world's first transnational alliance on compliant carbon markets,the coalition aims to coordinate carbon pricing mechanisms,emission trading systems and related policies in various countries,and realize the interconnection of global compliance carbon market networks.展开更多
Changes in the soil environment induced by major global changes in climate are affecting carbon emissions in cold-temperate coniferous forests.A randomized block experiment simulating warming,rainfall increase and nit...Changes in the soil environment induced by major global changes in climate are affecting carbon emissions in cold-temperate coniferous forests.A randomized block experiment simulating warming,rainfall increase and nitrogen addition in a Larix gmelinii forest was carried out to study the effects on soil carbon,nitrogen,and CO_(2)flux during the thawing,growing,and freezing periods.Our study found that warming(0-2.0℃)increased soil organic carbon(SOC)and total nitrogen(STN),dissolved organic carbon(DOC)and dissolved organic nitrogen(DON),and microbial biomass carbon(MBC)and microbial biomass nitrogen(MBN).Warming played a direct role in regulating soil CO_(2)emissions,stimulated microbial and plant root respiration and soil CO_(2)flux rapidly increased.Rainfall increase initially increased soil carbon and nitrogen,but a 30%increase in mean annual rainfall caused losses of SOC,STN,DOC,and DON,while MBC and MBN accumulated.Soil CO_(2)emissions were regulated by MBC after an increase in rainfall,excess moisture inhibited microbial activity,and soil CO_(2)flux showed a trend of R2(20%rainfall increase)>R1(10%rainfall increase)>CK(control)>R3(30%rainfall increase).The addition of nitrogen increased SOC,STN,DOC,DON,MBC and MBN.Soil CO_(2)flux progressively decreased with nitrogen inputs(2.5,5.0 and 10.0 g m^(-2)a^(-1)),as more N intensified plant-microbe competition.Nitrogen addition indirectly regulated soil CO_(2)emissions by altering SOC and STN,with MBC and MBN acting as secondary regulators.The results highlight the role of cold-temperate coniferous forest soils in predicting carbon-climate feedback in high-latitude forest permafrost regions.展开更多
Based on monthly runoff and climate datasets spanning 2000–2024,this study employed the Theil–Sen’s slope estimation,Mann–Kendall(M–K)trend test,as well as Pearson correlation and Spearman rank correlation analys...Based on monthly runoff and climate datasets spanning 2000–2024,this study employed the Theil–Sen’s slope estimation,Mann–Kendall(M–K)trend test,as well as Pearson correlation and Spearman rank correlation analyses to systematically examine the spatiotemporal patterns of runoff and its climatic driving mechanisms across Tajikistan,providing a scientific basis for sustainable water resource utilization and management in the study area.Results indicated that during 2000–2024,the annual runoff in Tajikistan exhibited statistically non-significant long-term trend(P=0.76),while displaying pronounced seasonal variability and strong spatial heterogeneity.Spring and summer average runoff primarily exhibited slight declining tendencies,while winter average runoff exhibited pronounced reduction in localized regions,such as the Syr Darya Basin,the Vakhsh River Basin,and the lower reaches of the Zeravshan River Basin.Precipitation emerged as the dominant positive driver of runoff,exhibiting moderate to strong positive correlations across over 78.00%of the country,whereas potential evapotranspiration consistently functioned as a negative driver.Rising temperatures exerted a dual competitive effect on runoff:in high-elevation,glacier-covered regions,rising temperatures temporarily increased runoff by accelerating glacier melt;however,at the national scale,the negative impact of rising temperature on runoff has played a slightly dominant role to a certain extent by enhancing evapotranspiration.Collectively,these results indicated that the present stability of runoff in Tajikistan is strongly dependent on the short-term compensatory effects of glacier melt and the risk of future runoff decline is likely to intensify as glacier reserves continue to diminish.This study provides a critical scientific evidence to inform sustainable water resource management in Tajikistan and underscores the need for glacier conservation and integrated water resource management strategies.展开更多
The hydrological system in Central Asia is highly sensitive to global climate change,significantly affecting water supply and energy production.In Tajikistan,the Vakhsh River—one of the main tributaries of the Amu Da...The hydrological system in Central Asia is highly sensitive to global climate change,significantly affecting water supply and energy production.In Tajikistan,the Vakhsh River—one of the main tributaries of the Amu Darya—plays a key role in the region’s hydropower and irrigation.However,research on long-term hydrological changes in its two top large basins—the Surkhob and Khingov river basins—remains limited.Therefore,this study analyzed long-term climate and hydrological changes in the Vakhsh River,including its main tributaries—the Surkhob and Khingov rivers—which are vital for the water resource management in Tajikistan and even in Central Asia.Using long-term hydrometeorological observations,the change trends of temperature(1933–2020),precipitation(1970–2020),and runoff(1940–2018)were examined to assess the impact of climate change on the regional water resources.The analysis revealed the occurrence of significant warming and a spatially uneven increase in precipitation.The temperature changes across three climatic periods(1933–1960,1960–1990,and 1990–2020)indicated that there was a transition from baseline level to accelerated warming.The precipitation showed a 2.99 mm/a increase in the Khingov River Basin and a 2.80 mm/a increase in the Surkhob River Basin during 1970–2020.Moreover,there was a gradual shift toward wetter conditions in recent decades.Despite the relatively stable annual mean runoff,seasonal redistribution occurred,with increased runoff in spring and reduced runoff in summer,due to the compensation of glacier melting.Moreover,this study forecasted runoff change during 2019–2040 using the exponential triple smoothing(ETS)method and revealed the occurrence of alternating wet and dry phases,emphasizing the sensitivity of the Vakhsh River Basin’s hydrological system to climate change and the necessity of adaptive water resource management in mountainous regions of Central Asia.Therefore,this study can provide evidence-based insights that are critical for future water resources planning,climate-resilient hydropower development,and regional adaptation strategies in climate-vulnerable basins in Central Asia.展开更多
In the northern Tarim River Basin,the Weigan River Basin is a critical endorheic system characterized by extreme aridity,where drought poses a major natural hazard to agricultural production and ecological stability.T...In the northern Tarim River Basin,the Weigan River Basin is a critical endorheic system characterized by extreme aridity,where drought poses a major natural hazard to agricultural production and ecological stability.This study assessed the future evolution of drought under climate change by employing the standardized moisture anomaly index(SZI)on the basis of multi-model the Coupled Model Intercomparison Project Phase 6(CMIP6)simulations under historical conditions(1970–2014)and future scenarios(shared socioeconomic pathway(SSP)1-2.6,SSP2-4.5,SSP3-7.0 and SSP5-8.5 for 2015–2100).The results show that precipitation–evapotranspiration anomalies are projected to first decline but then increase over time,with increased fluctuations and uncertainty under high-emission scenarios(SSP5-8.5).These trends indicate intensifying drought risks and reveal a strong influence of emission pathways on regional water cycling.Temporal analysis of SZI indicates a transition from wetting to drying under lowand medium-emission pathways(SSP1-2.6 and SSP2-4.5),whereas high-emission scenarios are characterized by persistent drying and increased variability.The significant lower-tail dependence(0.271)observed under SSP2-4.5 and SSP5-8.5 suggests that extreme droughts may be subject to nonlinear co-amplification across scenarios.The frequency of moderate and more severe drought events is expected to increase substantially,especially under SSP5-8.5,where drought occurrence is predicted to extend into spring and autumn and become more evenly distributed throughout the year.Spatially,drought duration shows significant positive autocorrelation across all scenarios,with hot spots consistently concentrated in the southern and southeastern regions of the basin.Random forest analysis,interpreted as association-based pattern attribution,indicates that meteorological variables(precipitation and potential evapotranspiration(PET))make the greatest contributions to the hot spot pattern,followed by topography and soil moisture.Among land use categories,farmland generally shows higher drought sensitivity than other land use types,as reflected by its relative contribution patterns across scenarios.The spatial pattern of drought is statistically structured by climatic forcing,surface conditions,and soil moisture status,reflecting their coupled associations with hot spot occurrence.In addition,a drought spatial uncertainty index was constructed from multi-scenario hot spot maps,revealing spatially heterogeneous structural variability throughout the basin.Correlation analysis further highlights strong internal couplings among environmental variables(e.g.,elevation-linked hydroclimatic gradients and grassland–bare soil contrasts).These findings offer a scientific basis for developing region-specific drought monitoring and adaptation strategies under future climate change conditions.展开更多
Fire is a fundamental ecological driver shaping natural vegetation patterns.In the semi-arid southern Espinal-Monte ecotone of Argentina,the spatiotemporal patterns of fire occurrence related to and modulated by clima...Fire is a fundamental ecological driver shaping natural vegetation patterns.In the semi-arid southern Espinal-Monte ecotone of Argentina,the spatiotemporal patterns of fire occurrence related to and modulated by climatic gradients and antecedent conditions are not well researched.This study examined fire occurrence in the semi-arid southern Espinal-Monte ecotone(southeastern La Pampa,northeastern Río Negro,and southwestern Buenos Aires with an area of 68×103 km2)of Argentina,a key environmental transition zone with pronounced climatic and vegetation gradients.The objective was to identify the spatiotemporal patterns of fire occurrence and their relationship with climatic variables.Thermal anomaly(TA)data from the MODIS(Moderate Resolution Imaging Spectrometer;MOD14)sensor(November 2000–March 2020)with confidence levels>65.0%were analyzed.Climatic variables(rainfall isohyets and aridity indices)were obtained from the WorldClim datasets,and annual meteorological conditions(rainfall and potential evapotranspiration)were calculated using the climatic research unit(CRU)database.Monthly data and moving averages of rainfall and aridity indices from distinct periods(two and three years preceding fire events)were integrated.Spatial analysis was conducted using kernel density estimation on a 10 km×10 km grid to correlate TA with climatic gradients,while linear regression examined relationships between summer TA and meteorological variables over different periods.Results showed that the highest fire occurrence was recorded in summer,with peaks in December and January.Spatially,55.0%of TA occurred in areas with annual rainfall of 300–400 mm,and 64.5%in areas with an aridity index of 0.3–0.4,forming an arc-like distribution in the center of the ecotone.The highest TA densities were observed in southeastern La Pampa and northeastern Río Negro,decreasing toward southwestern Buenos Aires.Significant correlations(R2>0.700)were found among TA accumulation,aridity index values,and cumulative rainfall from previous two and three years,at both vegetation unit and provincial levels.Summer was the critical season for fire occurrence,with spatial distribution primarily determined by the interaction between climatic conditions and woody biomass availability.The lower fire incidence in southwestern Buenos Aires was linked to sparse woody vegetation and agricultural expansion,which reduced fuel load.These findings reinforce that fuel availability,modulated by climatic conditions from previous years,is a key limiting factor for fire dynamics in this area,and that human activities such as agriculture and grazing alter fire regimes by affecting fuel structure and continuity.展开更多
Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regime...Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regimes and hydrological extremes to inform long-term water resources management strategies for the Kupang Catchment.Utilizing precipitation and air temperature data from general circulation models in the Coupled Model Intercomparison Project 6(CMIP6)and employing bias correction techniques,the Soil and Water Assessment Tool(SWAT)hydrological model was employed to analyze climate-induced changes in hydrological fluxes,specifically streamflow.Results indicated a consistent increase in monthly streamflow during the wet season,with a substantial rise of 22.8%,alongside a slight decrease of 18.0%during the dry season.Moreover,both the frequency and severity of extremely low and high flows were projected to intensify by approximately 50%and 70%,respectively,for a 20-year return period,suggesting heightened flood and drought risks in the future.The observed declining trend in low flow,by up to 11%,indicated the potential for long-term groundwater depletion exacerbating the threat of land subsidence and coastal flooding,especially in areas with inadequate surface water management policies and infrastructure.展开更多
Aboveground biomass(AGB)and belowground biomass(BGB)are key components of carbon storage,yet their responses to future climate changes remain poorly understood,particularly in China.Understanding these dynamics is ess...Aboveground biomass(AGB)and belowground biomass(BGB)are key components of carbon storage,yet their responses to future climate changes remain poorly understood,particularly in China.Understanding these dynamics is essential for global carbon cycle modeling and ecosystem management.This study integrates field observations,machine learning,and multi-source remote sensing data to reconstruct the distributions of AGB and BGB in China from 2000 to 2020.Then CMIP6 was used to predict the distribution of China under three SSP scenarios(SSP1-1.9,SSP2-4.5,SSP5-8.5)from 2020 to 2100 to fill the existing knowledge gap.The predictive accuracy for AGB(R^(2)=0.85)was significantly higher than for BGB(R^(2)=0.48),likely due to the greater complexity of modeling belowground dynamics.NDVI(Normalized Difference Vegetation Index)and soil organic carbon density(SOC)were identified as the primary drivers of AGB and BGB changes.During 2000-2020,AGB in China remained stable at approximately 10.69 Pg C,while BGB was around 5.06 Pg C.Forest ecosystems contributed 88.52% of AGB and 43.83% of BGB.AGB showed a relatively slow annual increase,while BGB demonstrated a significant annual growth rate of approximately 37 Tg C yr^(−1).Under the low-emission scenario,both AGB and BGB show fluctuations and steady growth,particularly in South China and the northwestern part of Northeast China.Under the moderate-emission scenario,AGB and BGB show significant declines and increases,respectively.In the high-emission scenario,both AGB and BGB decline significantly,particularly in the southwestern and central regions.These results provide valuable insights into ecosystem carbon dynamics under climate change,emphasizing the relatively low responsiveness of AGB and BGB to climatic variability,and offering guidance for sustainable land use and management strategies.展开更多
Agricultural pests cause enormous losses in annual agricultural production.Understanding the evolutionary responses and adaptive capacity of agricultural pests under climate change is crucial for establishing sustaina...Agricultural pests cause enormous losses in annual agricultural production.Understanding the evolutionary responses and adaptive capacity of agricultural pests under climate change is crucial for establishing sustainable and environmentally friendly agricultural pest management.In this study,we integrate climate modeling and landscape genomics to investigate the distributional dynamics of the cotton bollworm(Helicoverpa armigera)in the adaptation to local environments and resilience to future climate change.Notably,the predicted inhabitable areas with higher suitability for the cotton bollworm could be eight times larger in the coming decades.Climate change is one of the factors driving the dynamics of distribution and population differentiation of the cotton bollworm.Approximately 19,000 years ago,the cotton bollworm expanded from its ancestral African population,followed by gradual occupations of the European,Asian,Oceanian,and American continents.Furthermore,we identify seven subpopulations with high dispersal and adaptability which may have an increased risk of invasion potential.Additionally,a large number of candidate genes and SNPs linked to climatic adaptation were mapped.These findings could inform sustainable pest management strategies in the face of climate change,aiding future pest forecasting and management planning.展开更多
Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air poll...Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air pollution is crucial for mitigating climate change,improving air quality,and promoting the sustainable development of food systems.However,the literature lacks a comprehensive review of these interactions,particularly in the current phase of rapid development in the field.To address this gap,this study systematically reviews recent research on the impacts of climate change and air pollution on food systems,as well as the greenhouse gas and air pollutant emissions from agri-food systems and their contribution to global climate change and air pollution.In addition,this study summarizes various strategies for mitigation and adaptation,including adjustments in agricultural practices and food supply chains.Profound changes in food systems are urgently needed to enhance adaptability and reduce emissions.This review offers a critical overview of current research on the interactions among food systems,climate change,and air pollution and highlights future research directions to support the transition to sustainable food systems.展开更多
Carbon fluxes are essential indicators assessing vegetation carbon cycle functions.However,the extent and mechanisms by which climate change and human activities influence the spatiotemporal dynamics of carbon fluxes ...Carbon fluxes are essential indicators assessing vegetation carbon cycle functions.However,the extent and mechanisms by which climate change and human activities influence the spatiotemporal dynamics of carbon fluxes in arid oasis and non-oasis area remains unclear.Here,we assessed and predicted the future effects of climate change and human activities on carbon fluxes in the Hexi Corridor.The results showed that the annual average gross primary productivity(GPP),net ecosystem productivity(NEP),and ecosystem respiration(Reco)in the Hexi Corridor oasis increased by 263.91 g C·m^(-2)·yr^(-1),118.45 g C·m^(-2)·yr^(-1)and 122.46 g C·m^(-2)·yr^(-1),respectively,due to the expansion of the oasis area by 3424.84 km^(2) caused by human activities from 2000 to 2022.Both oasis and non-oasis arid ecosystems in the Hexi Corridor acted as carbon sinks.Compared to the non-oasis area,the carbon fluxes contributions of oasis area increased,ranging from 10.21%to 13.99%for GPP,8.50%to11.68%for NEP,and 13.34%to 17.13%for Reco.The contribution of the carbon flux from the oasis expansion area to the total carbon flux change in the Hexi Corridor was 30.96%(7.09 Tg C yr^(-1))for GPP,29.57%(3.39 Tg C yr^(-1))for NEP and 32.40%(3.58 Tg C yr^(-1))for Reco.The changes in carbon fluxes in the oasis area were mainly attributed to human activities(oasis expansion)and temperature,whereas non-oasis area was mainly due to climate factors.Moreover,the future increasing trends were observed for GPP(64.99%),NEP(66.29%)and Reco(82.08%)in the Hexi Corridor.This study provides new insights into the regulatory mechanisms of carbon cycle in the arid oasis and non-oasis area.展开更多
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supported by the JOINT CAS-MPG Research Project(Grant No.HZXM20225001MI)the National Natural Science Foundation of China(Grant No.W2412056,42271116 and 32100373)the China Biodiversity Observation Networks(Sino BON)。
文摘Climate change is altering vegetation phenology,differentially affecting food quality and availability for the gosling development(and therefore fitness)of migratory herbivores,especially those experiencing range contraction and fragmentation.By quantifying the climate-vegetation nexus for two waterbird species of contrasting conservation status,we assessed the differential implications of climate change in semi-arid landscapes for gosling development windows in different parts of their mid-latitude breeding ranges.We defined breeding ranges using telemetry data from 663 summering tracks of tagged Swan Geese(Anser cygnoides)and Greylag Geese(A.anser)breeding across the Mongolian Plateau.Within these areas,we systematically analyzed spatiotemporal variations in vegetation phenology based on MODIS NDVI datasets from 2000 to 2024 and their response to climate factors.Combining the above data,we demonstrated synchrony between goose breeding phenology and vegetation phenological indices:gosling hatching coincided with the start of growing season(SOS),autumn migration initiation with the end of growing season(EOS).We determined temporal and geographical variation in vegetation SOS,EOS and the length of growing season(LOS=EOS-SOS)as a proxy for gosling development windows across the Mongolian Plateau.Mean LOS was 107±13 days,generally sufficient for gosling development(c.113 days),but showed spatial heterogeneity,increasing in the west but shortening in the east of Mongolian Plateau.SOS was delayed with higher land surface temperature and lower precipitation/aridity in central/eastern Mongolian Plateau,but advanced in the west.Elevation of these three climatic factors delayed EOS across Mongolian Plateau.Climate warming and hydric stress may trigger synergistic SOS-delay and EOS-advance effects in the central and eastern Mongolian Plateau,increasing differential phenological mismatch risks to offspring fitness,thereby potentially affecting population growth rates and distributions.
基金supported by the Royal Thai Government Scholarship in Science and Technologythe Faculty of Environment and Resource Studies, Mahidol University, Thailand (FERS, Mahidol University)
文摘Land degradation,coupled with climate change impacts,poses serious threats to global land health and human well-being.Participatory scenario planning(PSP)has become a key tool for exploring these interconnected challenges;however,its progress and effectiveness remain underexplored.This study reviews 46 papers,using PRISMA guidelines,to investigate how PSP supports sustainable land management and climate resilience.We document how PSP applications have evolved from a biophysical focus to one addressing broader environmental,societal,and economic challenges.Disparities in how participants engage across PSP phases document the need for more equitable and meaningful participation.Clustering future scenarios reveals the complex interconnections among ecological,social,and economic factors underpinning land management and climate resilience,underscoring the need for inclusive and integrated strategies.From the emerging trends,we identify opportunities to advance PSP implementation,including early engagement of decision-makers,balanced representation and equitable power dynamics,meaningful participation,cross-disciplinary collaboration,integration of human-nature relationships,and regular revision of future pathways.Overall,our review highlights PSP’s potential to co-create inclusive,equitable scenarios and actionable pathways towards sustainable and resilient land use futures.
基金J.YANG was supported by funding from the National Natural Science Foundation of China(Grant Nos.42475022,42261144671)the National Key R&D Program of China(Project No.2024YFC3013100)+2 种基金the Fundamental Research Funds for the Central UniversitiesM.LU was supported by the Otto Poon Centre of Climate Resilience and Sustainability at HKUST and the Hong Kong Research Grant Committee(Project No.16300424)Data processing and storage were supported by the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulation Facility”(EarthLab).
文摘Precise forecasts of wildfire danger are crucial for proactive fuel management and emergency responses,yet they pose a challenge at the subseasonal scale due to limitations in prediction capabilities and a gap between forecast outputs and the needs of decision-makers.This study introduces an innovative hybrid modeling framework that integrates artificial intelligence(AI)with climate dynamic prediction systems to accurately forecast High Fire-Danger Days(HFDDs)for the following month.These HFDDs are derived from historical satellite fire data and the optimum fire danger index,with a particular focus on Southwest China as a case study.The AI module,based on the ResNet-18 neural network model,integrates observational and physically constrained analysis to establish links between HFDDs and optimal predictors of atmospheric circulation from both the concurrent and preceding months.Leveraging climate dynamical forecasting,this hybrid model provides more reliable deterministic predictions for monthly HFDDs than conventional methods that rely solely on terrestrial variables such as precipitation.More importantly,the integration of dynamical ensemble prediction enhances the model’s capability for skillful probabilistic predictions of HFDDs,facilitating the creation of customized fire danger outlooks and emergency action maps tailored to stakeholders’needs.The model’s added economic value was also evaluated,demonstrating its potential to improve decision-making in disaster management and bridge the“last-mile gap”in climate service delivery.This work contributes to the Seamless Prediction and Services for Sustainable Natural and Built Environment(SEPRESS)Program(2025–32),under the United Nations Educational Scientific and Cultural Organization(UNESCO)International Decade of Sciences for Sustainable Development(2024–33).
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the University of Milan for funding the“ProForesta”project through the 2020 Research Support Planthe“Ente Parco Nazionale dell'Appennino Tosco-Emiliano”for having financed the project“First urgent measures to promote the adaptation of the silver fir forests of the Tuscan-Emilian Apennine National Park to the effects of climate change”。
文摘Understanding how genetic variation within forest species influences growth responses under climate change is essential for improving the accuracy of forest models and guiding adaptive management strategies.This study models the dynamics of Italian silver fir(Abies alba)forests under varying climate change scenarios using the forest gap model FORMIND.Focusing on three distinct silver fir provenances(Western Alps,Northern Apennines,and Southern Apennines),the study simulates forest growth in the Tuscan-Emilian Apennine National Park under different representative concentration pathways(RCPs).The individual-based model FORMIND was parameterized and validated with field data for each of the provenances,demonstrating its ability to accurately reproduce key forest metrics and dynamics.Our results reveal significant differences in expected growth patterns,productivity,metabolism,and carbon storage capacity among the silver fir provenances in pure and mixed stands.In the simulations,the Northern Apennines provenance showed higher biomass production(biomass>10%±1%)and carbon uptake(net primary productivity,NPP>8%±1%)at the end of the century compared to the Western Alps provenance in the pure provenance(PP)and no regeneration scenario.Conversely,the Southern Apennines provenance showed higher biomass(biomass>5%–10%)and NPP(>15%–18%)in mixed provenance(MP)and regeneration scenarios.These results show that genetic diversity strongly affects forest growth and resilience to environmental changes.Hence,it should be included as a predictor variable in forest models.The study also demonstrates the resilience of silver fir to climatic stressors,emphasizing its potential as a robust species in multiple forest contexts.The integration of forest provenance data into the FORMIND model represents a significant advancement in forest modelling,enabling more accurate and reliable predictions under climate change scenarios.The study's findings advocate for a greater understanding and consideration of genetic diversity in forest management and conservation strategies,in support of assisted migration strategies aiming to enhance the resilience of forest ecosystems in a changing climate.
基金supported by a National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(Grant No.RS-2024-00342219)the Korea Meteorological Administration Research and Development Program(Grant No.RS-2025-02313090)S.-Y.JUN and B.-J.PARK were supported by Korea Polar Research Institute(KOPRI)grants funded by the Ministry of Oceans and Fisheries(Grant No.KOPRI PE25010).
文摘Climate change poses significant risks to agriculture,particularly in East Asia,a major crop-producing region.This study evaluates the effectiveness of near-term climate predictions in forecasting agricultural thermal conditions in East Asia for up to five years.We compare temperature-based agroclimatic indicators from atmospheric reanalysis data with the firstyear prediction of the Decadal Prediction System version 4(DePreSys4),initialized annually from November 1960 to 2024.Our analysis reveals that first-year predictions accurately represent observed spatial climatological patterns,although trends in agroclimatic indicators based on daily maximum temperature are overestimated.High skill scores are observed in predicting the beginning of the growing season,frost-free days,agricultural hot days,and heat intensity in major cropping regions.However,the end of the growing season is less predictable due to longer lead times.Notably,five-year average predictions show higher skill than first-year predictions due to smoothed interannual variability.These improved climate predictions enable farmers and policymakers to make informed decisions about crop selection and agricultural infrastructure.
文摘This study examined the role of green energy development in mitigating climate change and fostering sustainable development in Central Asia including Kazakhstan,Uzbekistan,Kyrgyzstan,Tajikistan,and Turkmenistan.The region has substantial untapped potential in solar energy,wind energy,hydropower energy,as well as biomass and bioenergy,positioning it strategically for renewable energy deployment.The result demonstrated that integrating renewable energy can reduce greenhouse gas emissions,improve air quality,enhance energy security,and support rural development.Case studies from Kazakhstan,Uzbekistan,Kyrgyzstan,and Tajikistan showed measurable environmental and economic benefits.However,the large-scale use of renewable energy still faces numerous barriers,including outdated infrastructure,fragmented regulatory frameworks,limited investment,and shortages of technical expertise.Overcoming these obstacles requires institutional reform,stronger regional cooperation,and increasing engagement from international financial institutions and private investors.Modernizing grids,deploying storage systems,and investing in education,research,and innovation are critical for building human capacity in renewable energy sector.Accelerating the renewable energy transition is essential for Central Asia to meet climate goals,enhance environmental resilience,and ensure long-term socioeconomic development through innovation,investment,and regional collaboration.
基金Supported by the National Key Research and Development Program of China(No.2023YFD2400800)the Laoshan Laboratory(Nos.LSKJ202203801,LSKJ202203204)+4 种基金the Natural Science Foundation of Shandong Province(Nos.ZR2023MD127,ZR2021MD075)the Central Public-interest Scientific Institution Basal Research Fund CAFS(Nos.2023TD28,20603022023012)the National Natural Science Foundation of China(No.32373107)the China Agriculture Research System(No.CARS-50)the Taishan Scholars Program。
文摘Giant kelp Macrocystis pyrifera,an important foundation species with great ecological and economic value,is threatened by climate change.To better understand the impact of climate warming on M.pyrifera,we investigated its global distribution dynamics by an optimized species distribution model(SDM).Results showed that wave height,sea surface temperature,benthic temperature,and benthic phosphate concentration were key factors shaping the distribution of M.pyrifera.In addition to currently known distribution regions,the model revealed potential suitable habitats globally.Under future climate scenarios,the habitat suitability of M.pyrifera would decrease at low latitudes and increase at high latitudes,resulting in a poleward shift of suitable habitats.In the regions currently occupied by M.pyrifera,the high suitable habitats were predicted to shrink,which implies that the existing M.pyrifera would be adversely impacted.These results serve as references for the conservation and utilization of M.pyrifera resource.
文摘Two international conferences in November 2025 jointly outlined a profound transformation of climate governance.The Committee on Trade and Environment(CTE)of the World Trade Organization(WTO)held a conference in Geneva,Switzerland,on November 4,where the topic of cooperation on trade-related carbon standards aroused heated discussions.The Leaders'Summit of the 30th Conference of the Parties(COP)to the UN Framework Convention on Climate Change(UNFCCC)was held in Belém,Brazil,on November 7.At the meeting,the Open Coalition on Compliance Carbon Markets was officially launched with the initial membership of 11 economies including Brazil,China,and the EU.As the world's first transnational alliance on compliant carbon markets,the coalition aims to coordinate carbon pricing mechanisms,emission trading systems and related policies in various countries,and realize the interconnection of global compliance carbon market networks.
基金funded by the Science and Technology Programme of Inner Mongolia Autonomous Region(Grant No.:2023YFDZ0026 and 2024KYPT0003)the 2024 Postgraduate Research and Innovation Programme of Inner Mongolia Agricultural University。
文摘Changes in the soil environment induced by major global changes in climate are affecting carbon emissions in cold-temperate coniferous forests.A randomized block experiment simulating warming,rainfall increase and nitrogen addition in a Larix gmelinii forest was carried out to study the effects on soil carbon,nitrogen,and CO_(2)flux during the thawing,growing,and freezing periods.Our study found that warming(0-2.0℃)increased soil organic carbon(SOC)and total nitrogen(STN),dissolved organic carbon(DOC)and dissolved organic nitrogen(DON),and microbial biomass carbon(MBC)and microbial biomass nitrogen(MBN).Warming played a direct role in regulating soil CO_(2)emissions,stimulated microbial and plant root respiration and soil CO_(2)flux rapidly increased.Rainfall increase initially increased soil carbon and nitrogen,but a 30%increase in mean annual rainfall caused losses of SOC,STN,DOC,and DON,while MBC and MBN accumulated.Soil CO_(2)emissions were regulated by MBC after an increase in rainfall,excess moisture inhibited microbial activity,and soil CO_(2)flux showed a trend of R2(20%rainfall increase)>R1(10%rainfall increase)>CK(control)>R3(30%rainfall increase).The addition of nitrogen increased SOC,STN,DOC,DON,MBC and MBN.Soil CO_(2)flux progressively decreased with nitrogen inputs(2.5,5.0 and 10.0 g m^(-2)a^(-1)),as more N intensified plant-microbe competition.Nitrogen addition indirectly regulated soil CO_(2)emissions by altering SOC and STN,with MBC and MBN acting as secondary regulators.The results highlight the role of cold-temperate coniferous forest soils in predicting carbon-climate feedback in high-latitude forest permafrost regions.
基金funded by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB0720203)the National Key Research and Development Program of China(2023YFF0805603).
文摘Based on monthly runoff and climate datasets spanning 2000–2024,this study employed the Theil–Sen’s slope estimation,Mann–Kendall(M–K)trend test,as well as Pearson correlation and Spearman rank correlation analyses to systematically examine the spatiotemporal patterns of runoff and its climatic driving mechanisms across Tajikistan,providing a scientific basis for sustainable water resource utilization and management in the study area.Results indicated that during 2000–2024,the annual runoff in Tajikistan exhibited statistically non-significant long-term trend(P=0.76),while displaying pronounced seasonal variability and strong spatial heterogeneity.Spring and summer average runoff primarily exhibited slight declining tendencies,while winter average runoff exhibited pronounced reduction in localized regions,such as the Syr Darya Basin,the Vakhsh River Basin,and the lower reaches of the Zeravshan River Basin.Precipitation emerged as the dominant positive driver of runoff,exhibiting moderate to strong positive correlations across over 78.00%of the country,whereas potential evapotranspiration consistently functioned as a negative driver.Rising temperatures exerted a dual competitive effect on runoff:in high-elevation,glacier-covered regions,rising temperatures temporarily increased runoff by accelerating glacier melt;however,at the national scale,the negative impact of rising temperature on runoff has played a slightly dominant role to a certain extent by enhancing evapotranspiration.Collectively,these results indicated that the present stability of runoff in Tajikistan is strongly dependent on the short-term compensatory effects of glacier melt and the risk of future runoff decline is likely to intensify as glacier reserves continue to diminish.This study provides a critical scientific evidence to inform sustainable water resource management in Tajikistan and underscores the need for glacier conservation and integrated water resource management strategies.
基金supported by the National Natural Science Foundation of China(W2412135).
文摘The hydrological system in Central Asia is highly sensitive to global climate change,significantly affecting water supply and energy production.In Tajikistan,the Vakhsh River—one of the main tributaries of the Amu Darya—plays a key role in the region’s hydropower and irrigation.However,research on long-term hydrological changes in its two top large basins—the Surkhob and Khingov river basins—remains limited.Therefore,this study analyzed long-term climate and hydrological changes in the Vakhsh River,including its main tributaries—the Surkhob and Khingov rivers—which are vital for the water resource management in Tajikistan and even in Central Asia.Using long-term hydrometeorological observations,the change trends of temperature(1933–2020),precipitation(1970–2020),and runoff(1940–2018)were examined to assess the impact of climate change on the regional water resources.The analysis revealed the occurrence of significant warming and a spatially uneven increase in precipitation.The temperature changes across three climatic periods(1933–1960,1960–1990,and 1990–2020)indicated that there was a transition from baseline level to accelerated warming.The precipitation showed a 2.99 mm/a increase in the Khingov River Basin and a 2.80 mm/a increase in the Surkhob River Basin during 1970–2020.Moreover,there was a gradual shift toward wetter conditions in recent decades.Despite the relatively stable annual mean runoff,seasonal redistribution occurred,with increased runoff in spring and reduced runoff in summer,due to the compensation of glacier melting.Moreover,this study forecasted runoff change during 2019–2040 using the exponential triple smoothing(ETS)method and revealed the occurrence of alternating wet and dry phases,emphasizing the sensitivity of the Vakhsh River Basin’s hydrological system to climate change and the necessity of adaptive water resource management in mountainous regions of Central Asia.Therefore,this study can provide evidence-based insights that are critical for future water resources planning,climate-resilient hydropower development,and regional adaptation strategies in climate-vulnerable basins in Central Asia.
基金supported by the Key Research and Development Project of Xinjiang Uygur Autonomous Region,China(2022B02049)the Major Science and Technology Special Project of Xinjiang Uygur Autonomous Region,China(2024A03007-5).
文摘In the northern Tarim River Basin,the Weigan River Basin is a critical endorheic system characterized by extreme aridity,where drought poses a major natural hazard to agricultural production and ecological stability.This study assessed the future evolution of drought under climate change by employing the standardized moisture anomaly index(SZI)on the basis of multi-model the Coupled Model Intercomparison Project Phase 6(CMIP6)simulations under historical conditions(1970–2014)and future scenarios(shared socioeconomic pathway(SSP)1-2.6,SSP2-4.5,SSP3-7.0 and SSP5-8.5 for 2015–2100).The results show that precipitation–evapotranspiration anomalies are projected to first decline but then increase over time,with increased fluctuations and uncertainty under high-emission scenarios(SSP5-8.5).These trends indicate intensifying drought risks and reveal a strong influence of emission pathways on regional water cycling.Temporal analysis of SZI indicates a transition from wetting to drying under lowand medium-emission pathways(SSP1-2.6 and SSP2-4.5),whereas high-emission scenarios are characterized by persistent drying and increased variability.The significant lower-tail dependence(0.271)observed under SSP2-4.5 and SSP5-8.5 suggests that extreme droughts may be subject to nonlinear co-amplification across scenarios.The frequency of moderate and more severe drought events is expected to increase substantially,especially under SSP5-8.5,where drought occurrence is predicted to extend into spring and autumn and become more evenly distributed throughout the year.Spatially,drought duration shows significant positive autocorrelation across all scenarios,with hot spots consistently concentrated in the southern and southeastern regions of the basin.Random forest analysis,interpreted as association-based pattern attribution,indicates that meteorological variables(precipitation and potential evapotranspiration(PET))make the greatest contributions to the hot spot pattern,followed by topography and soil moisture.Among land use categories,farmland generally shows higher drought sensitivity than other land use types,as reflected by its relative contribution patterns across scenarios.The spatial pattern of drought is statistically structured by climatic forcing,surface conditions,and soil moisture status,reflecting their coupled associations with hot spot occurrence.In addition,a drought spatial uncertainty index was constructed from multi-scenario hot spot maps,revealing spatially heterogeneous structural variability throughout the basin.Correlation analysis further highlights strong internal couplings among environmental variables(e.g.,elevation-linked hydroclimatic gradients and grassland–bare soil contrasts).These findings offer a scientific basis for developing region-specific drought monitoring and adaptation strategies under future climate change conditions.
基金funded by the National University of Río Negro Research Project (40-C-658)
文摘Fire is a fundamental ecological driver shaping natural vegetation patterns.In the semi-arid southern Espinal-Monte ecotone of Argentina,the spatiotemporal patterns of fire occurrence related to and modulated by climatic gradients and antecedent conditions are not well researched.This study examined fire occurrence in the semi-arid southern Espinal-Monte ecotone(southeastern La Pampa,northeastern Río Negro,and southwestern Buenos Aires with an area of 68×103 km2)of Argentina,a key environmental transition zone with pronounced climatic and vegetation gradients.The objective was to identify the spatiotemporal patterns of fire occurrence and their relationship with climatic variables.Thermal anomaly(TA)data from the MODIS(Moderate Resolution Imaging Spectrometer;MOD14)sensor(November 2000–March 2020)with confidence levels>65.0%were analyzed.Climatic variables(rainfall isohyets and aridity indices)were obtained from the WorldClim datasets,and annual meteorological conditions(rainfall and potential evapotranspiration)were calculated using the climatic research unit(CRU)database.Monthly data and moving averages of rainfall and aridity indices from distinct periods(two and three years preceding fire events)were integrated.Spatial analysis was conducted using kernel density estimation on a 10 km×10 km grid to correlate TA with climatic gradients,while linear regression examined relationships between summer TA and meteorological variables over different periods.Results showed that the highest fire occurrence was recorded in summer,with peaks in December and January.Spatially,55.0%of TA occurred in areas with annual rainfall of 300–400 mm,and 64.5%in areas with an aridity index of 0.3–0.4,forming an arc-like distribution in the center of the ecotone.The highest TA densities were observed in southeastern La Pampa and northeastern Río Negro,decreasing toward southwestern Buenos Aires.Significant correlations(R2>0.700)were found among TA accumulation,aridity index values,and cumulative rainfall from previous two and three years,at both vegetation unit and provincial levels.Summer was the critical season for fire occurrence,with spatial distribution primarily determined by the interaction between climatic conditions and woody biomass availability.The lower fire incidence in southwestern Buenos Aires was linked to sparse woody vegetation and agricultural expansion,which reduced fuel load.These findings reinforce that fuel availability,modulated by climatic conditions from previous years,is a key limiting factor for fire dynamics in this area,and that human activities such as agriculture and grazing alter fire regimes by affecting fuel structure and continuity.
基金supported by the funding Riset Unggulan Daerah 2022 of the Bureau of Development Planning and Research in Central Java Province(BAPPEDA Provinsi Jawa Tengah).
文摘Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regimes and hydrological extremes to inform long-term water resources management strategies for the Kupang Catchment.Utilizing precipitation and air temperature data from general circulation models in the Coupled Model Intercomparison Project 6(CMIP6)and employing bias correction techniques,the Soil and Water Assessment Tool(SWAT)hydrological model was employed to analyze climate-induced changes in hydrological fluxes,specifically streamflow.Results indicated a consistent increase in monthly streamflow during the wet season,with a substantial rise of 22.8%,alongside a slight decrease of 18.0%during the dry season.Moreover,both the frequency and severity of extremely low and high flows were projected to intensify by approximately 50%and 70%,respectively,for a 20-year return period,suggesting heightened flood and drought risks in the future.The observed declining trend in low flow,by up to 11%,indicated the potential for long-term groundwater depletion exacerbating the threat of land subsidence and coastal flooding,especially in areas with inadequate surface water management policies and infrastructure.
基金supported by the Tianchi Talent-Young Doctor Program of the Xinjiang Uygur Autonomous Region,the Innovation Training Program for Undergraduates at the Autonomous Region Level in 2024(Grant No.S202410755009)the Innovation Training Program for Undergraduates at the University Level in 2024(Grant No.XJU-SRT-24008)+3 种基金the National Innovation Training Program for College Students in 2024(Grant No.202410755009)the National Natural Science Foundation of China(Grant No.42401065)the Basic and Applied Basic Research Program of Guangdong Province,China(Grant No.2023A1515011273)the Research Projects of the Department of Education of Guangdong Province(Grant No.2023KTSCX315).
文摘Aboveground biomass(AGB)and belowground biomass(BGB)are key components of carbon storage,yet their responses to future climate changes remain poorly understood,particularly in China.Understanding these dynamics is essential for global carbon cycle modeling and ecosystem management.This study integrates field observations,machine learning,and multi-source remote sensing data to reconstruct the distributions of AGB and BGB in China from 2000 to 2020.Then CMIP6 was used to predict the distribution of China under three SSP scenarios(SSP1-1.9,SSP2-4.5,SSP5-8.5)from 2020 to 2100 to fill the existing knowledge gap.The predictive accuracy for AGB(R^(2)=0.85)was significantly higher than for BGB(R^(2)=0.48),likely due to the greater complexity of modeling belowground dynamics.NDVI(Normalized Difference Vegetation Index)and soil organic carbon density(SOC)were identified as the primary drivers of AGB and BGB changes.During 2000-2020,AGB in China remained stable at approximately 10.69 Pg C,while BGB was around 5.06 Pg C.Forest ecosystems contributed 88.52% of AGB and 43.83% of BGB.AGB showed a relatively slow annual increase,while BGB demonstrated a significant annual growth rate of approximately 37 Tg C yr^(−1).Under the low-emission scenario,both AGB and BGB show fluctuations and steady growth,particularly in South China and the northwestern part of Northeast China.Under the moderate-emission scenario,AGB and BGB show significant declines and increases,respectively.In the high-emission scenario,both AGB and BGB decline significantly,particularly in the southwestern and central regions.These results provide valuable insights into ecosystem carbon dynamics under climate change,emphasizing the relatively low responsiveness of AGB and BGB to climatic variability,and offering guidance for sustainable land use and management strategies.
基金funded by the National Natural Science Foundation of China(32372546)Shenzhen Science and Technology Program(KQTD20180411143628272)+1 种基金the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences and STI 2030-Major Projects(2022ZD04021)the National Key Research and Development Program of China(2023YFD2200700)。
文摘Agricultural pests cause enormous losses in annual agricultural production.Understanding the evolutionary responses and adaptive capacity of agricultural pests under climate change is crucial for establishing sustainable and environmentally friendly agricultural pest management.In this study,we integrate climate modeling and landscape genomics to investigate the distributional dynamics of the cotton bollworm(Helicoverpa armigera)in the adaptation to local environments and resilience to future climate change.Notably,the predicted inhabitable areas with higher suitability for the cotton bollworm could be eight times larger in the coming decades.Climate change is one of the factors driving the dynamics of distribution and population differentiation of the cotton bollworm.Approximately 19,000 years ago,the cotton bollworm expanded from its ancestral African population,followed by gradual occupations of the European,Asian,Oceanian,and American continents.Furthermore,we identify seven subpopulations with high dispersal and adaptability which may have an increased risk of invasion potential.Additionally,a large number of candidate genes and SNPs linked to climatic adaptation were mapped.These findings could inform sustainable pest management strategies in the face of climate change,aiding future pest forecasting and management planning.
基金supported by the National Natural Science Foundation of China(42277087,42130708,42471021,42277482,and 42361144876)the Natural Science Foundation of Guangdong Province(2024A1515012550)+3 种基金the Hainan Institute of National Park grant(KY-23ZK01)the Tsinghua Shenzhen International Graduate School Cross-disciplinary Research and Innovation Fund Research Plan(JC2022011)the Shenzhen Science and Technology Program(JCYJ20240813112106009 and ZDSYS20220606100806014)the Scientific Research Start-up Funds(QD2021030C)from Tsinghua Shenzhen International Graduate School。
文摘Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air pollution is crucial for mitigating climate change,improving air quality,and promoting the sustainable development of food systems.However,the literature lacks a comprehensive review of these interactions,particularly in the current phase of rapid development in the field.To address this gap,this study systematically reviews recent research on the impacts of climate change and air pollution on food systems,as well as the greenhouse gas and air pollutant emissions from agri-food systems and their contribution to global climate change and air pollution.In addition,this study summarizes various strategies for mitigation and adaptation,including adjustments in agricultural practices and food supply chains.Profound changes in food systems are urgently needed to enhance adaptability and reduce emissions.This review offers a critical overview of current research on the interactions among food systems,climate change,and air pollution and highlights future research directions to support the transition to sustainable food systems.
基金The Foundation for Distinguished Young Scholars of Gansu Province,No.22JR5RA046Key Research Program of Gansu Province,No.23ZDKA0004+2 种基金The Joint Funds of the National Natural Science Foundation of China,No.U22A202690Interdisciplinary Youth Team Project from the Key Laboratory of Cryospheric Science and Frozen Soil Engineering,No.CSFSE-ZQ-2408The Youth Innovation Promotion Association CAS to X.W.,No.2020422。
文摘Carbon fluxes are essential indicators assessing vegetation carbon cycle functions.However,the extent and mechanisms by which climate change and human activities influence the spatiotemporal dynamics of carbon fluxes in arid oasis and non-oasis area remains unclear.Here,we assessed and predicted the future effects of climate change and human activities on carbon fluxes in the Hexi Corridor.The results showed that the annual average gross primary productivity(GPP),net ecosystem productivity(NEP),and ecosystem respiration(Reco)in the Hexi Corridor oasis increased by 263.91 g C·m^(-2)·yr^(-1),118.45 g C·m^(-2)·yr^(-1)and 122.46 g C·m^(-2)·yr^(-1),respectively,due to the expansion of the oasis area by 3424.84 km^(2) caused by human activities from 2000 to 2022.Both oasis and non-oasis arid ecosystems in the Hexi Corridor acted as carbon sinks.Compared to the non-oasis area,the carbon fluxes contributions of oasis area increased,ranging from 10.21%to 13.99%for GPP,8.50%to11.68%for NEP,and 13.34%to 17.13%for Reco.The contribution of the carbon flux from the oasis expansion area to the total carbon flux change in the Hexi Corridor was 30.96%(7.09 Tg C yr^(-1))for GPP,29.57%(3.39 Tg C yr^(-1))for NEP and 32.40%(3.58 Tg C yr^(-1))for Reco.The changes in carbon fluxes in the oasis area were mainly attributed to human activities(oasis expansion)and temperature,whereas non-oasis area was mainly due to climate factors.Moreover,the future increasing trends were observed for GPP(64.99%),NEP(66.29%)and Reco(82.08%)in the Hexi Corridor.This study provides new insights into the regulatory mechanisms of carbon cycle in the arid oasis and non-oasis area.
