Over the last three decades,more than half of the world's large lakes and wetlands have experienced significant shrinkage,primarily due to climate change and extensive water consumption for agriculture and other h...Over the last three decades,more than half of the world's large lakes and wetlands have experienced significant shrinkage,primarily due to climate change and extensive water consumption for agriculture and other human needs.The desiccation of lakes leads to severe environmental,economic,and social repercussions.Urmia Lake,located in northwestern Iran and representing a vital natural ecosystem,has experienced a volume reduction of over 90.0%.Our research evaluated diverse water management strategies within the Urmia Lake basin and prospects of inter-basin water transfers.This study focused on strategies to safeguard the environmental water rights of the Urmia Lake by utilizing the modeling and simulating(MODSIM)model.The model simulated changes in the lake's water volume under various scenarios.These included diverting water from incoming rivers,cutting agricultural water use by 40.0%,releasing dam water in non-agricultural seasons,treated wastewater utilization,and inter-basin transfers.Analytical hierarchy process(AHP)was utilized to analyze the simulation results.Expert opinions with AHP analysis,acted as a multi-criteria decision-making tool to evaluate the simulation and determine the optimal water supply source priority for the Urmia Lake.Our findings underscore the critical importance of reducing agricultural water consumption as the foremost step in preserving the lake.Following this,inter-basin water transfers are suggested,with a detailed consideration of the inherent challenges and limitations faced by the source watersheds.It is imperative to conduct assessments on the impacts of these transfers on the downstream users and the potential environmental risks,advocating for a diplomatic and cooperative approach with adjacent country.This study also aims to forecast the volumes of water that can be transferred under different climatic conditions—drought,normal,and wet years—to inform strategic water management planning for the Urmia Lake.According to our projection,implementing the strategic scenarios outlined could significantly augment the lake's level and volume,potentially by 3.57×109–9.38×109 m3 over the coming 10 a and 3.57×109–10.70×109 m3 in the subsequent 15 a.展开更多
Atmospheric phenomena are physical phenomena resulting from the correlation of atmospheric parameters of natural origin. They are associated with climatic storms and include lightning, thunder, global warming, wind, e...Atmospheric phenomena are physical phenomena resulting from the correlation of atmospheric parameters of natural origin. They are associated with climatic storms and include lightning, thunder, global warming, wind, evaporation, rain, clouds, and snow. The formation and evolution of these phenomena remain complex according to their natural reference parameters. The numerical models defined in this study are equations based on models of atmospheric parameters. Applied in the atmosphere, they yield the equation of the key atmospheric phenomena. The distribution of these phenomena across the entire planet is the origin of the formation of climatic regions. Indeed, the constants obtained are 275.16 km/s for the speed of lightning, 3.99 GJ for the discharge energy of a thunderbolt, 276.15˚K for the temperature of global warming, 3.993 Km/h for the formation speed of winds and cyclones, 2.9963 Km/h for the speed of evaporation, 278.16˚K for the formation of rain, 274.1596˚K for the formation of clouds, and 274.1632˚K for snow formation. Moreover, this research conducts an analytical study approach to the phenomenon of climate change in the current era of industrialization, specifically analyzing the direct effects of global warming on atmospheric phenomena. Thus, with a temperature of 53.45˚C, global warming is considered maximal and will lead to very abundant rain and snow precipitations with maximum PW at 12.5 and 11.1 g/cm2 of water, surface water evaporation fluxes significantly above normal at a speed of 6.55 Km/h, increasingly violent winds at speeds far exceeding 5.43 Km/h, and catastrophic climatic effects. In summary, the aim of this research is to define the main natural phenomena associated with global climatic storms and to study the real impact of climate change on Earth.展开更多
The Yellow River Basin(YRB)has experienced severe floods and continuous riverbed elevation throughout history.Global climate change has been suggested to be driving a worldwide increase in flooding risk.However,owing ...The Yellow River Basin(YRB)has experienced severe floods and continuous riverbed elevation throughout history.Global climate change has been suggested to be driving a worldwide increase in flooding risk.However,owing to insufficient evidence,the quantitative correlation between flooding and climate change remains illdefined.We present a long time series of maximum flood discharge in the YRB dating back to 1843 compiled from historical documents and instrument measurements.Variations in yearly maximum flood discharge show distinct periods:a dramatic decreasing period from 1843 to 1950,and an oscillating gentle decreasing from 1950 to 2021,with the latter period also showing increasing more extreme floods.A Mann-Kendall test analysis suggests that the latter period can be further split into two distinct sub-periods:an oscillating gentle decreasing period from 1950 to 2000,and a clear recent increasing period from 2000 to 2021.We further predict that climate change will cause an ongoing remarkable increase in future flooding risk and an∼44.4 billion US dollars loss of floods in the YRB in 2100.展开更多
The alpine meadow ecosystem accounts for 27%of the total area of the Tibetan Plateau and is also one of the most important vegetation types.The Dangxiong alpine meadow ecosystem,located in the south-central part of th...The alpine meadow ecosystem accounts for 27%of the total area of the Tibetan Plateau and is also one of the most important vegetation types.The Dangxiong alpine meadow ecosystem,located in the south-central part of the Tibetan Plateau,is a typical example.To understand the carbon and water fluxes,water use efficiency(WUE),and their responses to future climate change for the alpine meadow ecosystem in the Dangxiong area,two parameter estimation methods,the Model-independent Parameter Estimation(PEST)and the Dynamic Dimensions Search(DDS),were used to optimize the Biome-BGC model.Then,the gross primary productivity(GPP)and evapotranspiration(ET)were simulated.The results show that the DDS parameter calibration method has a better performance.The annual GPP and ET show an increasing trend,while the WUE shows a decreasing trend.Meanwhile,ET and GPP reach their peaks in July and August,respectively,and WUE shows a“dual-peak”pattern,reaching peaks in May and November.Furthermore,according to the simulation results for the next nearly 100 years,the ensemble average GPP and ET exhibit a significant increasing trend,and the growth rate under the SSP5–8.5 scenario is greater than that under the SSP2–4.5 scenario.WUE shows an increasing trend under the SSP2–4.5 scenario and a significant increasing trend under the SSP5–8.5 scenario.This study has important scientific significance for carbon and water cycle prediction and vegetation ecological protection on the Tibetan Plateau.展开更多
Vegetation greening has long been acknowledged,but recent studies have pointed out that vegetation greening is possibly stalled or even reversed.However,detailed analyses about greening reversal or increased browning ...Vegetation greening has long been acknowledged,but recent studies have pointed out that vegetation greening is possibly stalled or even reversed.However,detailed analyses about greening reversal or increased browning of vegetation remain scarce.In this study,we utilized the normalized difference vegetation index(NDVI)as an indicator of vegetation to investigate the trends of vegetation greening and browning(monotonic,interruption,and reversal)through the breaks for the additive season and trend(BFAST)method across China’s drylands from 1982 to 2022.It also reveals the impacts of ecological restoration programs(ERPs)and climate change on these vegetation trends.We find that the vegetation displays an obvious pattern of east-greening and west-browning in China’s drylands.Greening trends mainly exhibits monotonic greening(29.8%)and greening with setback(36.8%),whereas browning shows a greening to browning reversal(19.2%).The increase rate of greening to browning reversal is 0.0342/yr,which is apparently greater than that of greening with setback,0.0078/yr.This research highlights that,under the background of widespread vegetation greening,vegetation browning is pro-gressively increasing due to the effects of climate change.Furthermore,the ERPs have significantly increased vegetation coverage,with the increase rate in 2000-2022 being twice as much as that of 1982-1999 in reveg-etation regions.Vegetation browning in southwestern Qingzang Plateau is primarily driven by adverse climatic factors and anthropogenic disturbances,which offset the efforts of ERPs.展开更多
Gross primary productivity(GPP)of vegetation is an important constituent of the terrestrial carbon sinks and is significantly influenced by drought.Understanding the impact of droughts on different types of vegetation...Gross primary productivity(GPP)of vegetation is an important constituent of the terrestrial carbon sinks and is significantly influenced by drought.Understanding the impact of droughts on different types of vegetation GPP provides insight into the spatiotemporal variation of terrestrial carbon sinks,aiding efforts to mitigate the detrimental effects of climate change.In this study,we utilized the precipitation and temperature data from the Climatic Research Unit,the standardized precipitation evapotranspiration index(SPEI),the standardized precipitation index(SPI),and the simulated vegetation GPP using the eddy covariance-light use efficiency(EC-LUE)model to analyze the spatiotemporal change of GPP and its response to different drought indices in the Mongolian Plateau during 1982-2018.The main findings indicated that vegetation GPP decreased in 50.53% of the plateau,mainly in its northern and northeastern parts,while it increased in the remaining 49.47%area.Specifically,meadow steppe(78.92%)and deciduous forest(79.46%)witnessed a significant decrease in vegetation GPP,while alpine steppe(75.08%),cropland(76.27%),and sandy vegetation(87.88%)recovered well.Warming aridification areas accounted for 71.39% of the affected areas,while 28.53% of the areas underwent severe aridification,mainly located in the south and central regions.Notably,the warming aridification areas of desert steppe(92.68%)and sandy vegetation(90.24%)were significant.Climate warming was found to amplify the sensitivity of coniferous forest,deciduous forest,meadow steppe,and alpine steppe GPP to drought.Additionally,the drought sensitivity of vegetation GPP in the Mongolian Plateau gradually decreased as altitude increased.The cumulative effect of drought on vegetation GPP persisted for 3.00-8.00 months.The findings of this study will improve the understanding of how drought influences vegetation in arid and semi-arid areas.展开更多
Tree radial growth can have significantly differ-ent responses to climate change depending on the environ-ment.To elucidate the effects of climate on radial growth and stable carbon isotope(δ^(13)C)fractionation of Q...Tree radial growth can have significantly differ-ent responses to climate change depending on the environ-ment.To elucidate the effects of climate on radial growth and stable carbon isotope(δ^(13)C)fractionation of Qing-hai spruce(Picea crassifolia),a widely distributed native conifer in northwestern China in different environments,we developed chronologies for tree-ring widths and δ^(13)C in trees on the southern and northern slopes of the Qilian Mountains,and analysed the relationship between these tree-ring variables and major climatic factors.Tree-ring widths were strongly influenced by climatic factors early in the growing season,and the radial growth in trees on the northern slopes was more sensitive to climate than in trees on the southern.Tree-ring δ^(13)C was more sensitive to climate than radial growth.δ^(13)C fractionation was mainly influenced by summer temperature and precipitation early in the growing season.Stomatal conductance more strongly limited stable carbon isotope fractionation in tree rings than photosynthetic rate did.The response between tree rings and climate in mountains gradually weakened as climate warmed.Changes in radial growth and stable carbon isotope fractionation of P.crassifolia in response to climate in the Qilian Mountains may be further complicated by continued climate change.展开更多
Climate change and human activities such as overgrazing and rapid development of tourism simultaneously affected the vegetation of the Zoige Plateau.However,the spatiotemporal variations of vegetation and the relative...Climate change and human activities such as overgrazing and rapid development of tourism simultaneously affected the vegetation of the Zoige Plateau.However,the spatiotemporal variations of vegetation and the relative contributions of climate change and human activities to these vegetation dynamics remain unclear.Therefore,clarifying how and why the vegetation on the Zoige Plateau changed can provide a scientific basis for the sustainable development of the region.Here,we investigate NDVI trends using the Normalized Difference Vegetation Index(NDVI)as an indicator of vegetation greenness and distinguish the relative effects of climate changes and human activities on vegetation changes by utilizing residual trend analysis and the Geodetector.We find a tendency of vegetation greening from 2001 to 2020,with significant greening accounting for 21.44%of the entire region.However,browning area expanded rapidly after 2011.Warmer temperatures are the primary driver of vegetation changes in the Zoige Plateau.Climatic variations and human activities were responsible for 65.57%and 34.43%of vegetation greening,and 39.14%and 60.86%of vegetation browning,respectively,with browning concentrated along the Yellow,Black and White Rivers.Compared to 2001-2010,the inhibitory effect of human activity and climate fluctuations on vegetation grew dramatically between 2011 and 2020.展开更多
There has been an increasing recognition of the crucial role of forests, responsible for sequestering atmospheric CO_(2), as a moral imperative for mitigating the pace of climate change. The complexity of evaluating c...There has been an increasing recognition of the crucial role of forests, responsible for sequestering atmospheric CO_(2), as a moral imperative for mitigating the pace of climate change. The complexity of evaluating climate change impacts on forest carbon and water dynamics lies in the diverse acclimations of forests to changing environments. In this study, we assessed two of the most common acclimation traits, namely leaf area index and the maximum rate of carboxylation(V_(cmax)), to explore the potential acclimation pathways of Pinus koraiensis under climate change. We used a mechanistic and process-based ecohydrological model applied to a P. koraiensis forest in Mt. Taehwa, South Korea. We conducted numerical investigations into the impacts of(i) Shared Socioeconomic Pathways 2–4.5(SSP2-4.5) and 5–8.5(SSP5-8.5),(ii) elevated atmospheric CO_(2) and temperature, and(iii) acclimations of leaf area index and V_(cmax)on the carbon and water dynamics of P. koraiensis. We found that there was a reduction in net primary productivity(NPP) under the SSP2-4.5 scenario, but not under SSP5-8.5, compared to the baseline, due to an imbalance between increases in atmospheric CO_(2) and temperature. A decrease in leaf area index and an increase in V_(cmax)of P. koraiensis were expected if acclimations were made to reduce its leaf temperature. Under such acclimation pathways, it would be expected that the well-known CO_(2) fertilizer effects on NPP would be attenuated.展开更多
Central Asia consists of the former Soviet Republics,Kazakhstan,Kyrgyz Republic,Tajikistan,Turkmenistan,and Uzbekistan.The region’s climate is continental,mostly semi-arid to arid.Agriculture is a significant part of...Central Asia consists of the former Soviet Republics,Kazakhstan,Kyrgyz Republic,Tajikistan,Turkmenistan,and Uzbekistan.The region’s climate is continental,mostly semi-arid to arid.Agriculture is a significant part of the region’s economy.By its nature of intensive water use,agriculture is extremely vulnerable to climate change.Population growth and irrigation development have significantly increased the demand for water in the region.Major climate change issues include melting glaciers and a shrinking snowpack,which are the foundation of the region’s water resources,and a changing precipitation regime.Most glaciers are located in Kyrgyzstan and Tajikistan,leading to transboundary water resource issues.Summer already has extremely high temperatures.Analyses indicate that Central Asia has been warming and precipitation might be increasing.The warming is expected to increase,but its spatial and temporal distribution depends upon specific global scenarios.Projections of future precipitation show significant uncertainties in type,amount,and distribution.Regional Hydroclimate Projects(RHPs)are an approach to studying these issues.Initial steps to develop an RHP began in 2021 with a widely distributed online survey about these climate issues.It was followed up with an online workshop and then,in 2023,an in-person workshop,held in Tashkent,Uzbekistan.Priorities for the Global Energy and Water Exchanges(GEWEX)project for the region include both observations and modeling,as well as development of better and additional precipitation observations,all of which are topics for the next workshop.A well-designed RHP should lead to reductions in critical climate uncertainties in policy-relevant timeframes that can influence decisions on necessary investments in climate adaptation.展开更多
Temporal changes in the relationship between tree growth and climate have been observed in numerous forests across the world.The patterns and the possible regu-lators(e.g.,forest community structure)of such changes ar...Temporal changes in the relationship between tree growth and climate have been observed in numerous forests across the world.The patterns and the possible regu-lators(e.g.,forest community structure)of such changes are,however,not well understood.A vegetation survey and analyses of growth-climate relationships for Abies georgei var.Smithii(Smith fir)forests were carried along an altitudi-nal gradient from 3600 to 4200 m on Meili Snow Mountain,southeastern Tibetan Plateau.The results showed that the associations between growth and temperature have declined since the 1970s over the whole transect,while response to standardized precipitation-evapotranspiration indices(SPEI)strengthened in the mid-and lower-transect.Comparison between growth and vegetation data showed that tree growth was more sensitive to drought in stands with higher species richness and greater shrub cover.Drought stress on growth may be increased by heavy competition from shrub and herb layers.These results show the non-stationary nature of tree growth-climate associations and the linkage to for-est community structures.Vegetation components should be considered in future modeling and forecasting of forest dynamics in relation to climate changes.展开更多
Climate change poses a serious long-term threat to biodiversity.To effectively reduce biodiversity loss,conservationists need to have a thorough understanding of the preferred habitats of species and the variables tha...Climate change poses a serious long-term threat to biodiversity.To effectively reduce biodiversity loss,conservationists need to have a thorough understanding of the preferred habitats of species and the variables that affect their distribution.Therefore,predicting the impact of climate change on speciesappropriate habitats may help mitigate the potential threats to biodiversity distribution.Xerophyta,a monocotyledonous genus of the family Velloziaceae is native to mainland Africa,Madagascar,and the Arabian Peninsula.The key drivers of Xerophyta habitat distribution and preference are unknown.Using 308 species occurrence data and eight environmental variables,the MaxEnt model was used to determine the potential distribution of six Xerophyta species in Africa under past,current and future climate change scenarios.The results showed that the models had a good predictive ability(Area Under the Curve and True Skill Statistics values for all SDMs were more than 0.902),indicating high accuracy in forecasting the potential geographic distribution of Xerophyta species.The main bioclimatic variables that impacted potential distributions of most Xerophyta species were mean temperature of the driest quarter(Bio9)and precipitation of the warmest quarter(Bio18).According to our models,tropical Africa has zones of moderate and high suitability for Xerophyta taxa,which is consistent with the majority of documented species localities.The habitat suitability of the existing range of the Xerophyta species varied based on the climate scenario,with most species experiencing a range loss greater than the range gain regardless of the climate scenario.The projected spatiotemporal patterns of Xerophyta species help guide recommendations for conservation efforts.展开更多
Determining the suitable areas for winter wheat under climate change and assessing the risk of freezing injury are crucial for the cultivation of winter wheat.We used an optimized Maximum Entropy(MaxEnt)Model to predi...Determining the suitable areas for winter wheat under climate change and assessing the risk of freezing injury are crucial for the cultivation of winter wheat.We used an optimized Maximum Entropy(MaxEnt)Model to predict the potential distribution of winter wheat in the current period(1970-2020)and the future period(2021-2100)under four shared socioeconomic pathway scenarios(SSPs).We applied statistical downscaling methods to downscale future climate data,established a scientific and practical freezing injury index(FII)by considering the growth period of winter wheat,and analyzed the characteristics of abrupt changes in winter wheat freezing injury by using the Mann-Kendall(M-K)test.The results showed that the prediction accuracy AUC value of the MaxEnt Model reached 0.976.The minimum temperature in the coldest month,precipitation in the wettest season and annual precipitation were the main factors affecting the spatial distribution of winter wheat.The total suitable area of winter wheat was approximately 4.40×10^(7)ha in the current period.In the 2070s,the moderately suitable areas had the greatest increase by 9.02×10^(5)ha under SSP245 and the least increase by 6.53×10^(5)ha under SSP370.The centroid coordinates of the total suitable areas tended to move northward.The potential risks of freezing injury in the high-latitude and-altitude areas of the Loess Plateau,China increased significantly.The northern areas of Xinzhou in Shanxi Province,China suffered the most serious freezing injury,and the southern areas of the Loess Plateau suffered the least.Environmental factors such as temperature,precipitation and geographical location had important impacts on the suitable area distribution and freezing injury risk of winter wheat.In the future,greater attention should be paid to the northward boundaries of both the winter wheat planting areas and the areas of freezing injury risk to provide the early warning of freezing injury and implement corresponding management strategies.展开更多
The South China Sea is a hotspot for regional climate research.Over the past 40 years,considerable improvement has been made in the development and utilization of the islands in the South China Sea,leading to a substa...The South China Sea is a hotspot for regional climate research.Over the past 40 years,considerable improvement has been made in the development and utilization of the islands in the South China Sea,leading to a substantial change in the land-use of the islands.However,research on the impact of human development on the local climate of these islands is lacking.This study analyzed the characteristics of local climate changes on the islands in the South China Sea based on data from the Yongxing Island Observation Station and ERA5 re-analysis.Furthermore,the influence of urbanization on the local climate of the South China Sea islands was explored in this study.The findings revealed that the 10-year average temperature in Yongxing Island increased by approximately 1.11℃from 1961 to 2020,and the contribution of island development and urbanization to the local warming rate over 60 years was approximately 36.2%.The linear increasing trend of the annual hot days from 1961–2020 was approximately 14.84 days per decade.The diurnal temperature range exhibited an increasing trend of 0.05℃per decade,whereas the number of cold days decreased by 1.06days per decade.The rapid increase in construction on Yongxing Island from 2005 to 2021 led to a decrease in observed surface wind speed by 0.32 m s^(-1)per decade.Consequently,the number of days with strong winds decreased,whereas the number of days with weak winds increased.Additionally,relative humidity exhibited a rapid decline from 2001 to 2016 and then rebounded.The study also found substantial differences between the ERA5 re-analysis and observation data,particularly in wind speed and relative humidity,indicating that the use of re-analysis data for climate resource assessment and climate change evaluation on island areas may not be feasible.展开更多
The Qilian Mountains(QM)possess a delicate vegetation ecosystem,amplifying the evident response of vegetation phenology to climate change.The relationship between changes in vegetation growth and climate remains compl...The Qilian Mountains(QM)possess a delicate vegetation ecosystem,amplifying the evident response of vegetation phenology to climate change.The relationship between changes in vegetation growth and climate remains complex.To this end,we used MODIS NDVI data to extract the phenological parameters of the vegetation including meadow(MDW),grassland(GSD),and alpine vegetation(ALV))in the QM from 2002 to 2021.Then,we employed path analysis to reveal the direct and indirect impacts of seasonal climate change on vegetation phenology.Additionally,we decomposed the vegetation phenology in a time series using the trigonometric seasonality,Box-Cox transformation,ARMA errors,and Trend Seasonal components model(TBATS).The findings showed a distinct pattern in the vegetation phenology of the QM,characterized by a progressive shift towards an earlier start of the growing season(SOS),a delayed end of the growing season(EOS),and an extended length of the growing season(LOS).The growth cycle of MDW,GSD,and ALV in the QM species is clearly defined.The SOS for MDW and GSD occurred earlier,mainly between late April and August,while the SOS for ALVs occurred between mid-May and mid-August,a one-month delay compared to the other vegetation.The EOS in MDW and GSD were concentrated between late August and April and early September and early January,respectively.Vegetation phenology exhibits distinct responses to seasonal temperature and precipitation patterns.The advancement and delay of SOS were mainly influenced by the direct effect of spring temperatures and precipitation,which affected 19.59%and 22.17%of the study area,respectively.The advancement and delay of EOS were mainly influenced by the direct effect of fall temperatures and precipitation,which affected 30.18%and 21.17%of the area,respectively.On the contrary,the direct effects of temperature and precipitation in summer and winter on vegetation phenology seem less noticeable and were mainly influenced by indirect effects.The indirect effect of winter precipitation is the main factor affecting the advance or delay of SOS,and the area proportions were 16.29%and 23.42%,respectively.The indirect effects of fall temperatures and precipitation were the main factors affecting the delay and advancement of EOS,respectively,with an area share of 15.80%and 21.60%.This study provides valuable insight into the relationship between vegetation phenology and climate change,which can be of great practical value for the ecological protection of the Qinghai-Tibetan Plateau as well as for the development of GSD ecological animal husbandry in the QM alpine pastoral area.展开更多
The driving effects of climate change and human activities on vegetation change have always been a focal point of research.However,the coupling mechanisms of these driving factors across different temporal and spatial...The driving effects of climate change and human activities on vegetation change have always been a focal point of research.However,the coupling mechanisms of these driving factors across different temporal and spatial scales remain controversial.The Southwestern Alpine Canyon Region of China(SACR),as an ecologically fragile area,is highly sensitive to the impacts of climate change and human activities.This study constructed a vegetation cover dataset for the SACR based on the Enhanced Vegetation Index(EVI)from 2000 to 2020.Spatial autocorrelation,Theil-Sen trend,and Mann-Kendall tests were used to analyze the spatiotemporal characteristics of vegetation cover changes.The main drivers of spatial heterogeneity in vegetation cover were identified using the optimal parameter geographic detector,and an improved residual analysis model was employed to quantify the relative contributions of climate change and human activities to interannual vegetation cover changes.The main findings are as follows:Spatially,vegetation cover exceeds 60%in most areas,especially in the southern part of the study area.However,the border area between Linzhi and Changdu exhibits lower vegetation cover.Climate factors are the primary drivers of spatial heterogeneity in vegetation cover,with temperature having the most significant influence,as indicated by its q-value,which far exceeds that of other factors.Additionally,the interaction q-value between the two factors significantly increases,showing a relationship of bivariate enhancement and nonlinear enhancement.In terms of temporal changes,vegetation cover shows an overall improving trend from 2000 to 2020,with significant increases observed in 68.93%of the study area.Among these,human activities are the main factors driving vegetation cover change,with a relative contribution rate of 41.31%,while climate change and residual factors contribute 35.66%and 23.53%,respectively.By thoroughly exploring the coupled mechanisms of vegetation change,this study provides important references for the sustainable management and conservation of the vegetation ecosystem in the SACR.展开更多
Atmospheric deposition of nitrogen(N)plays a significant role in shaping the structure and functioning of various terrestrial ecosystems worldwide.However,the magnitude of N deposition on grassland ecosystems in Centr...Atmospheric deposition of nitrogen(N)plays a significant role in shaping the structure and functioning of various terrestrial ecosystems worldwide.However,the magnitude of N deposition on grassland ecosystems in Central Asia still remains highly uncertain.In this study,a multi-data approach was adopted to analyze the distribution and amplitude of N deposition effects in Central Asia from 1979 to 2014 using a process-based denitrification decomposition(DNDC)model.Results showed that total vegetation carbon(C)in Central Asia was 0.35(±0.09)Pg C/a and the averaged water stress index(WSI)was 0.20(±0.02)for the whole area.Increasing N deposition led to an increase in the vegetation C of 65.56(±83.03)Tg C and slightly decreased water stress in Central Asia.Findings of this study will expand both our understanding and predictive capacity of C characteristics under future increases in N deposition,and also serve as a valuable reference for decision-making regarding water resources management and climate change mitigation in arid and semi-arid areas globally.展开更多
Revegetation of former agricultural land is a key option for climate change mitigation and nature conservation.Expansion and abandonment of agricultural land is typically influenced by trends in diets and agricultural...Revegetation of former agricultural land is a key option for climate change mitigation and nature conservation.Expansion and abandonment of agricultural land is typically influenced by trends in diets and agricultural inten-sification,which are two key parameters in the Shared Socioeconomic Pathways(SSPs).Datasets mapping future land dynamics under different SSPs and climate change mitigation targets stem from different scenario assump-tions,land data and modelling frameworks.This study aims to determine the role that these three factors play in the estimates of the evolution of cropland and pastureland in future SSPs under different climate scenarios from four main datasets largely used in the climate and land surface studies.The datasets largely agree with the rep-resentation of cropland at present-day conditions,but the identification of pastureland is ambiguous and shows large discrepancies due to the lack of a unique land-use category.Differences occur with future projections,even for the same SSP and climate target.Accounting for CO_(2)sequestration from revegetation of abandoned agri-cultural land and CO_(2)emissions from forest clearance due to agricultural expansion shows a net reduction in vegetation carbon stock for most SSPs considered,except SSP1.However,different datasets give differences in estimates,even when representative of the same scenario.With SSP1,the cumulative increase in carbon stock until 2050 is 3.3 GtC for one dataset,and more than double for another.Our study calls for a common classifica-tion system with improved detection of pastureland to harmonize projections and reduce variability of outcomes in environmental studies.展开更多
Changing climate will jeopardize biodiversity,particularly the geographic distribution of endemic species.One such species is the Javan Hawk-Eagle(JHE,Nisaetus bartelsi),a charismatic raptor found only on Java Island,...Changing climate will jeopardize biodiversity,particularly the geographic distribution of endemic species.One such species is the Javan Hawk-Eagle(JHE,Nisaetus bartelsi),a charismatic raptor found only on Java Island,Indonesia.Thus,it is crucial to develop an appropriate conservation strategy to preserve the species.Ecological niche modeling is considered a valuable tool for designing conservation plans for the JHE.We provide an ecological niche modeling approach and transfer its model to future climate scenarios for the JHE.We utilize various machine learning algorithms under sustainability and business-as-usual(BAU)scenarios for 2050.Additionally,we investigate the conservation vulnerability of the JHE,capturing multifaceted pressures on the species from climate dissimilarities and human disturbance variables.Our study reveals that the ensemble model performs exceptionally well,with temperature emerging as the most critical factor affecting the JHE distribution.This finding indicates that climate change will have a significant impact on the JHE species.Our results suggest that the JHE distribution will likely decrease by 28.41%and 40.16%from the current JHE distribution under sustainability and BAU scenarios,respectively.Furthermore,our study reveals high-potential refugia for future JHE,covering 7,596 km^(2)(61%)under the sustainability scenario and only 4,403 km^(2)(35%)under the BAU scenario.Therefore,effective management and planning,including habitat restoration,refugia preservation,habitat connectivity,and local community inclusivity,should be well-managed to achieve JHE conservation targets.展开更多
Quercus arkansana(Arkansas oak)is at risk of becoming endangered,as the total known population size is represented by a few isolated populations.The potential impact of climate change on this species in the near futur...Quercus arkansana(Arkansas oak)is at risk of becoming endangered,as the total known population size is represented by a few isolated populations.The potential impact of climate change on this species in the near future is high,yet knowledge of its predicted effects is limited.Our study utilized the biomod2 R package to develop habi-tat suitability ensemble models based on bioclimatic and topographic environmental variables and the known loca-tions of current distribution of Q.arkansana.We predicted suitable habitats across three climate change scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5)for 2050,2070,and 2090.Our findings reveal that the current suitable habitat for Q.arkansana is approximately 127,881 km^(2) across seven states(Texas,Arkansas,Alabama,Louisiana,Mississippi,Georgia,and Florida);approximately 9.5%is encompassed within state and federally managed protected areas.Our models predict that all current suitable habitats will disap-pear by 2050 due to climate change,resulting in a northward shift into new regions such as Tennessee and Kentucky.The large extent of suitable habitat outside protected areas sug-gests that a species-specific action plan incorporating pro-tected areas and other areas may be crucial for its conserva-tion.Moreover,protection of Q.arkansana habitat against climate change may require locally and regionally focused conservation policies,adaptive management strategies,and educational outreach among local people.展开更多
文摘Over the last three decades,more than half of the world's large lakes and wetlands have experienced significant shrinkage,primarily due to climate change and extensive water consumption for agriculture and other human needs.The desiccation of lakes leads to severe environmental,economic,and social repercussions.Urmia Lake,located in northwestern Iran and representing a vital natural ecosystem,has experienced a volume reduction of over 90.0%.Our research evaluated diverse water management strategies within the Urmia Lake basin and prospects of inter-basin water transfers.This study focused on strategies to safeguard the environmental water rights of the Urmia Lake by utilizing the modeling and simulating(MODSIM)model.The model simulated changes in the lake's water volume under various scenarios.These included diverting water from incoming rivers,cutting agricultural water use by 40.0%,releasing dam water in non-agricultural seasons,treated wastewater utilization,and inter-basin transfers.Analytical hierarchy process(AHP)was utilized to analyze the simulation results.Expert opinions with AHP analysis,acted as a multi-criteria decision-making tool to evaluate the simulation and determine the optimal water supply source priority for the Urmia Lake.Our findings underscore the critical importance of reducing agricultural water consumption as the foremost step in preserving the lake.Following this,inter-basin water transfers are suggested,with a detailed consideration of the inherent challenges and limitations faced by the source watersheds.It is imperative to conduct assessments on the impacts of these transfers on the downstream users and the potential environmental risks,advocating for a diplomatic and cooperative approach with adjacent country.This study also aims to forecast the volumes of water that can be transferred under different climatic conditions—drought,normal,and wet years—to inform strategic water management planning for the Urmia Lake.According to our projection,implementing the strategic scenarios outlined could significantly augment the lake's level and volume,potentially by 3.57×109–9.38×109 m3 over the coming 10 a and 3.57×109–10.70×109 m3 in the subsequent 15 a.
文摘Atmospheric phenomena are physical phenomena resulting from the correlation of atmospheric parameters of natural origin. They are associated with climatic storms and include lightning, thunder, global warming, wind, evaporation, rain, clouds, and snow. The formation and evolution of these phenomena remain complex according to their natural reference parameters. The numerical models defined in this study are equations based on models of atmospheric parameters. Applied in the atmosphere, they yield the equation of the key atmospheric phenomena. The distribution of these phenomena across the entire planet is the origin of the formation of climatic regions. Indeed, the constants obtained are 275.16 km/s for the speed of lightning, 3.99 GJ for the discharge energy of a thunderbolt, 276.15˚K for the temperature of global warming, 3.993 Km/h for the formation speed of winds and cyclones, 2.9963 Km/h for the speed of evaporation, 278.16˚K for the formation of rain, 274.1596˚K for the formation of clouds, and 274.1632˚K for snow formation. Moreover, this research conducts an analytical study approach to the phenomenon of climate change in the current era of industrialization, specifically analyzing the direct effects of global warming on atmospheric phenomena. Thus, with a temperature of 53.45˚C, global warming is considered maximal and will lead to very abundant rain and snow precipitations with maximum PW at 12.5 and 11.1 g/cm2 of water, surface water evaporation fluxes significantly above normal at a speed of 6.55 Km/h, increasingly violent winds at speeds far exceeding 5.43 Km/h, and catastrophic climatic effects. In summary, the aim of this research is to define the main natural phenomena associated with global climatic storms and to study the real impact of climate change on Earth.
基金the National Natural Science Foundation of China(Grants No.42041006,41790443 and 41927806).
文摘The Yellow River Basin(YRB)has experienced severe floods and continuous riverbed elevation throughout history.Global climate change has been suggested to be driving a worldwide increase in flooding risk.However,owing to insufficient evidence,the quantitative correlation between flooding and climate change remains illdefined.We present a long time series of maximum flood discharge in the YRB dating back to 1843 compiled from historical documents and instrument measurements.Variations in yearly maximum flood discharge show distinct periods:a dramatic decreasing period from 1843 to 1950,and an oscillating gentle decreasing from 1950 to 2021,with the latter period also showing increasing more extreme floods.A Mann-Kendall test analysis suggests that the latter period can be further split into two distinct sub-periods:an oscillating gentle decreasing period from 1950 to 2000,and a clear recent increasing period from 2000 to 2021.We further predict that climate change will cause an ongoing remarkable increase in future flooding risk and an∼44.4 billion US dollars loss of floods in the YRB in 2100.
基金supported by the Second Comprehensive Scientific Research Survey on the Tibetan Plateau[grant number 2019QZKK0103]the National Natural Science Foundation of China[grant numbers 42375071 and 42230610].
文摘The alpine meadow ecosystem accounts for 27%of the total area of the Tibetan Plateau and is also one of the most important vegetation types.The Dangxiong alpine meadow ecosystem,located in the south-central part of the Tibetan Plateau,is a typical example.To understand the carbon and water fluxes,water use efficiency(WUE),and their responses to future climate change for the alpine meadow ecosystem in the Dangxiong area,two parameter estimation methods,the Model-independent Parameter Estimation(PEST)and the Dynamic Dimensions Search(DDS),were used to optimize the Biome-BGC model.Then,the gross primary productivity(GPP)and evapotranspiration(ET)were simulated.The results show that the DDS parameter calibration method has a better performance.The annual GPP and ET show an increasing trend,while the WUE shows a decreasing trend.Meanwhile,ET and GPP reach their peaks in July and August,respectively,and WUE shows a“dual-peak”pattern,reaching peaks in May and November.Furthermore,according to the simulation results for the next nearly 100 years,the ensemble average GPP and ET exhibit a significant increasing trend,and the growth rate under the SSP5–8.5 scenario is greater than that under the SSP2–4.5 scenario.WUE shows an increasing trend under the SSP2–4.5 scenario and a significant increasing trend under the SSP5–8.5 scenario.This study has important scientific significance for carbon and water cycle prediction and vegetation ecological protection on the Tibetan Plateau.
基金supported by the National Natural Science Foundation of China(Grants No.41991231,42041004,and 41888101)the China University Research Talents Recruitment Program(111 project,Grant No.B13045).
文摘Vegetation greening has long been acknowledged,but recent studies have pointed out that vegetation greening is possibly stalled or even reversed.However,detailed analyses about greening reversal or increased browning of vegetation remain scarce.In this study,we utilized the normalized difference vegetation index(NDVI)as an indicator of vegetation to investigate the trends of vegetation greening and browning(monotonic,interruption,and reversal)through the breaks for the additive season and trend(BFAST)method across China’s drylands from 1982 to 2022.It also reveals the impacts of ecological restoration programs(ERPs)and climate change on these vegetation trends.We find that the vegetation displays an obvious pattern of east-greening and west-browning in China’s drylands.Greening trends mainly exhibits monotonic greening(29.8%)and greening with setback(36.8%),whereas browning shows a greening to browning reversal(19.2%).The increase rate of greening to browning reversal is 0.0342/yr,which is apparently greater than that of greening with setback,0.0078/yr.This research highlights that,under the background of widespread vegetation greening,vegetation browning is pro-gressively increasing due to the effects of climate change.Furthermore,the ERPs have significantly increased vegetation coverage,with the increase rate in 2000-2022 being twice as much as that of 1982-1999 in reveg-etation regions.Vegetation browning in southwestern Qingzang Plateau is primarily driven by adverse climatic factors and anthropogenic disturbances,which offset the efforts of ERPs.
基金jointly supported by the National Natural Science Foundation of China(42361024,42101030,42261079,and 41961058)the Talent Project of Science and Technology in Inner Mongolia of China(NJYT22027 and NJYT23019)the Fundamental Research Funds for the Inner Mongolia Normal University,China(2022JBBJ014 and 2022JBQN093)。
文摘Gross primary productivity(GPP)of vegetation is an important constituent of the terrestrial carbon sinks and is significantly influenced by drought.Understanding the impact of droughts on different types of vegetation GPP provides insight into the spatiotemporal variation of terrestrial carbon sinks,aiding efforts to mitigate the detrimental effects of climate change.In this study,we utilized the precipitation and temperature data from the Climatic Research Unit,the standardized precipitation evapotranspiration index(SPEI),the standardized precipitation index(SPI),and the simulated vegetation GPP using the eddy covariance-light use efficiency(EC-LUE)model to analyze the spatiotemporal change of GPP and its response to different drought indices in the Mongolian Plateau during 1982-2018.The main findings indicated that vegetation GPP decreased in 50.53% of the plateau,mainly in its northern and northeastern parts,while it increased in the remaining 49.47%area.Specifically,meadow steppe(78.92%)and deciduous forest(79.46%)witnessed a significant decrease in vegetation GPP,while alpine steppe(75.08%),cropland(76.27%),and sandy vegetation(87.88%)recovered well.Warming aridification areas accounted for 71.39% of the affected areas,while 28.53% of the areas underwent severe aridification,mainly located in the south and central regions.Notably,the warming aridification areas of desert steppe(92.68%)and sandy vegetation(90.24%)were significant.Climate warming was found to amplify the sensitivity of coniferous forest,deciduous forest,meadow steppe,and alpine steppe GPP to drought.Additionally,the drought sensitivity of vegetation GPP in the Mongolian Plateau gradually decreased as altitude increased.The cumulative effect of drought on vegetation GPP persisted for 3.00-8.00 months.The findings of this study will improve the understanding of how drought influences vegetation in arid and semi-arid areas.
基金supported by Basic Research Operating Expenses of the Central level Non-profit Research Institutes (IDM2022003)National Natural Science Foundation of China (42375054)+2 种基金Regional collaborative innovation project of Xinjiang (2021E01022,2022E01045)Young Meteorological Talent Program of China Meteorological Administration,Tianshan Talent Program of Xinjiang (2022TSYCCX0003)Youth Innovation Team of China Meteorological Administration (CMA2023QN08).
文摘Tree radial growth can have significantly differ-ent responses to climate change depending on the environ-ment.To elucidate the effects of climate on radial growth and stable carbon isotope(δ^(13)C)fractionation of Qing-hai spruce(Picea crassifolia),a widely distributed native conifer in northwestern China in different environments,we developed chronologies for tree-ring widths and δ^(13)C in trees on the southern and northern slopes of the Qilian Mountains,and analysed the relationship between these tree-ring variables and major climatic factors.Tree-ring widths were strongly influenced by climatic factors early in the growing season,and the radial growth in trees on the northern slopes was more sensitive to climate than in trees on the southern.Tree-ring δ^(13)C was more sensitive to climate than radial growth.δ^(13)C fractionation was mainly influenced by summer temperature and precipitation early in the growing season.Stomatal conductance more strongly limited stable carbon isotope fractionation in tree rings than photosynthetic rate did.The response between tree rings and climate in mountains gradually weakened as climate warmed.Changes in radial growth and stable carbon isotope fractionation of P.crassifolia in response to climate in the Qilian Mountains may be further complicated by continued climate change.
基金partially financed by the National Natural Science Foundation of China(Grant No.42201439)Natural Science Foundation of Sichuan Provincial Department of Science and Technology(Grant No.2022NSFSC1082)Key Laboratory of Smart Earth(No.KF2023YB02-12).
文摘Climate change and human activities such as overgrazing and rapid development of tourism simultaneously affected the vegetation of the Zoige Plateau.However,the spatiotemporal variations of vegetation and the relative contributions of climate change and human activities to these vegetation dynamics remain unclear.Therefore,clarifying how and why the vegetation on the Zoige Plateau changed can provide a scientific basis for the sustainable development of the region.Here,we investigate NDVI trends using the Normalized Difference Vegetation Index(NDVI)as an indicator of vegetation greenness and distinguish the relative effects of climate changes and human activities on vegetation changes by utilizing residual trend analysis and the Geodetector.We find a tendency of vegetation greening from 2001 to 2020,with significant greening accounting for 21.44%of the entire region.However,browning area expanded rapidly after 2011.Warmer temperatures are the primary driver of vegetation changes in the Zoige Plateau.Climatic variations and human activities were responsible for 65.57%and 34.43%of vegetation greening,and 39.14%and 60.86%of vegetation browning,respectively,with browning concentrated along the Yellow,Black and White Rivers.Compared to 2001-2010,the inhibitory effect of human activity and climate fluctuations on vegetation grew dramatically between 2011 and 2020.
基金supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)(No.2021R1C1C1004801)。
文摘There has been an increasing recognition of the crucial role of forests, responsible for sequestering atmospheric CO_(2), as a moral imperative for mitigating the pace of climate change. The complexity of evaluating climate change impacts on forest carbon and water dynamics lies in the diverse acclimations of forests to changing environments. In this study, we assessed two of the most common acclimation traits, namely leaf area index and the maximum rate of carboxylation(V_(cmax)), to explore the potential acclimation pathways of Pinus koraiensis under climate change. We used a mechanistic and process-based ecohydrological model applied to a P. koraiensis forest in Mt. Taehwa, South Korea. We conducted numerical investigations into the impacts of(i) Shared Socioeconomic Pathways 2–4.5(SSP2-4.5) and 5–8.5(SSP5-8.5),(ii) elevated atmospheric CO_(2) and temperature, and(iii) acclimations of leaf area index and V_(cmax)on the carbon and water dynamics of P. koraiensis. We found that there was a reduction in net primary productivity(NPP) under the SSP2-4.5 scenario, but not under SSP5-8.5, compared to the baseline, due to an imbalance between increases in atmospheric CO_(2) and temperature. A decrease in leaf area index and an increase in V_(cmax)of P. koraiensis were expected if acclimations were made to reduce its leaf temperature. Under such acclimation pathways, it would be expected that the well-known CO_(2) fertilizer effects on NPP would be attenuated.
基金The National Research University Tashkent Institute of Irrigation and Agricultural Mechanization Engineers of Uzbekistan hosted and provided financial support for the in-person workshop in May of 2023
文摘Central Asia consists of the former Soviet Republics,Kazakhstan,Kyrgyz Republic,Tajikistan,Turkmenistan,and Uzbekistan.The region’s climate is continental,mostly semi-arid to arid.Agriculture is a significant part of the region’s economy.By its nature of intensive water use,agriculture is extremely vulnerable to climate change.Population growth and irrigation development have significantly increased the demand for water in the region.Major climate change issues include melting glaciers and a shrinking snowpack,which are the foundation of the region’s water resources,and a changing precipitation regime.Most glaciers are located in Kyrgyzstan and Tajikistan,leading to transboundary water resource issues.Summer already has extremely high temperatures.Analyses indicate that Central Asia has been warming and precipitation might be increasing.The warming is expected to increase,but its spatial and temporal distribution depends upon specific global scenarios.Projections of future precipitation show significant uncertainties in type,amount,and distribution.Regional Hydroclimate Projects(RHPs)are an approach to studying these issues.Initial steps to develop an RHP began in 2021 with a widely distributed online survey about these climate issues.It was followed up with an online workshop and then,in 2023,an in-person workshop,held in Tashkent,Uzbekistan.Priorities for the Global Energy and Water Exchanges(GEWEX)project for the region include both observations and modeling,as well as development of better and additional precipitation observations,all of which are topics for the next workshop.A well-designed RHP should lead to reductions in critical climate uncertainties in policy-relevant timeframes that can influence decisions on necessary investments in climate adaptation.
基金supported by the Second Tibetan Plateau Scientific Expedition and Research Program(2019QZKK0301)NationalNatural Science Foundation of China(32271886 and 42271074).
文摘Temporal changes in the relationship between tree growth and climate have been observed in numerous forests across the world.The patterns and the possible regu-lators(e.g.,forest community structure)of such changes are,however,not well understood.A vegetation survey and analyses of growth-climate relationships for Abies georgei var.Smithii(Smith fir)forests were carried along an altitudi-nal gradient from 3600 to 4200 m on Meili Snow Mountain,southeastern Tibetan Plateau.The results showed that the associations between growth and temperature have declined since the 1970s over the whole transect,while response to standardized precipitation-evapotranspiration indices(SPEI)strengthened in the mid-and lower-transect.Comparison between growth and vegetation data showed that tree growth was more sensitive to drought in stands with higher species richness and greater shrub cover.Drought stress on growth may be increased by heavy competition from shrub and herb layers.These results show the non-stationary nature of tree growth-climate associations and the linkage to for-est community structures.Vegetation components should be considered in future modeling and forecasting of forest dynamics in relation to climate changes.
基金supported by grants from the International Partnership Program of Chinese Academy of Sciences (151853KYSB20190027)Sino-Africa Joint Research Center, CAS (SAJC202101)The ANSO Scholarship for Young Talents, PhD Fellowship Program University of Chinese Academy of Sciences, China
文摘Climate change poses a serious long-term threat to biodiversity.To effectively reduce biodiversity loss,conservationists need to have a thorough understanding of the preferred habitats of species and the variables that affect their distribution.Therefore,predicting the impact of climate change on speciesappropriate habitats may help mitigate the potential threats to biodiversity distribution.Xerophyta,a monocotyledonous genus of the family Velloziaceae is native to mainland Africa,Madagascar,and the Arabian Peninsula.The key drivers of Xerophyta habitat distribution and preference are unknown.Using 308 species occurrence data and eight environmental variables,the MaxEnt model was used to determine the potential distribution of six Xerophyta species in Africa under past,current and future climate change scenarios.The results showed that the models had a good predictive ability(Area Under the Curve and True Skill Statistics values for all SDMs were more than 0.902),indicating high accuracy in forecasting the potential geographic distribution of Xerophyta species.The main bioclimatic variables that impacted potential distributions of most Xerophyta species were mean temperature of the driest quarter(Bio9)and precipitation of the warmest quarter(Bio18).According to our models,tropical Africa has zones of moderate and high suitability for Xerophyta taxa,which is consistent with the majority of documented species localities.The habitat suitability of the existing range of the Xerophyta species varied based on the climate scenario,with most species experiencing a range loss greater than the range gain regardless of the climate scenario.The projected spatiotemporal patterns of Xerophyta species help guide recommendations for conservation efforts.
基金supported by the National Natural Science Foundation of China(31201168)the Basic Research Program of Shanxi Province,China(20210302123411)the earmarked fund for Modern Agro-industry Technology Research System,China(2022-07).
文摘Determining the suitable areas for winter wheat under climate change and assessing the risk of freezing injury are crucial for the cultivation of winter wheat.We used an optimized Maximum Entropy(MaxEnt)Model to predict the potential distribution of winter wheat in the current period(1970-2020)and the future period(2021-2100)under four shared socioeconomic pathway scenarios(SSPs).We applied statistical downscaling methods to downscale future climate data,established a scientific and practical freezing injury index(FII)by considering the growth period of winter wheat,and analyzed the characteristics of abrupt changes in winter wheat freezing injury by using the Mann-Kendall(M-K)test.The results showed that the prediction accuracy AUC value of the MaxEnt Model reached 0.976.The minimum temperature in the coldest month,precipitation in the wettest season and annual precipitation were the main factors affecting the spatial distribution of winter wheat.The total suitable area of winter wheat was approximately 4.40×10^(7)ha in the current period.In the 2070s,the moderately suitable areas had the greatest increase by 9.02×10^(5)ha under SSP245 and the least increase by 6.53×10^(5)ha under SSP370.The centroid coordinates of the total suitable areas tended to move northward.The potential risks of freezing injury in the high-latitude and-altitude areas of the Loess Plateau,China increased significantly.The northern areas of Xinzhou in Shanxi Province,China suffered the most serious freezing injury,and the southern areas of the Loess Plateau suffered the least.Environmental factors such as temperature,precipitation and geographical location had important impacts on the suitable area distribution and freezing injury risk of winter wheat.In the future,greater attention should be paid to the northward boundaries of both the winter wheat planting areas and the areas of freezing injury risk to provide the early warning of freezing injury and implement corresponding management strategies.
基金National Natural Science Foundation of China(U21A6001,42075059)Specific Research Fund of The Innovation Platform for Academicians of Hainan Province(YSPTZX202143)+1 种基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)Science and Technology Project of Guangdong Meteorological Service(GRMC2020M29)。
文摘The South China Sea is a hotspot for regional climate research.Over the past 40 years,considerable improvement has been made in the development and utilization of the islands in the South China Sea,leading to a substantial change in the land-use of the islands.However,research on the impact of human development on the local climate of these islands is lacking.This study analyzed the characteristics of local climate changes on the islands in the South China Sea based on data from the Yongxing Island Observation Station and ERA5 re-analysis.Furthermore,the influence of urbanization on the local climate of the South China Sea islands was explored in this study.The findings revealed that the 10-year average temperature in Yongxing Island increased by approximately 1.11℃from 1961 to 2020,and the contribution of island development and urbanization to the local warming rate over 60 years was approximately 36.2%.The linear increasing trend of the annual hot days from 1961–2020 was approximately 14.84 days per decade.The diurnal temperature range exhibited an increasing trend of 0.05℃per decade,whereas the number of cold days decreased by 1.06days per decade.The rapid increase in construction on Yongxing Island from 2005 to 2021 led to a decrease in observed surface wind speed by 0.32 m s^(-1)per decade.Consequently,the number of days with strong winds decreased,whereas the number of days with weak winds increased.Additionally,relative humidity exhibited a rapid decline from 2001 to 2016 and then rebounded.The study also found substantial differences between the ERA5 re-analysis and observation data,particularly in wind speed and relative humidity,indicating that the use of re-analysis data for climate resource assessment and climate change evaluation on island areas may not be feasible.
基金financially supported by the National Natural Sciences Foundation of China(42261026,41971094,and 42161025)Gansu Science and Technology Research Project(22ZD6FA005)+1 种基金Higher Education Innovation Foundation of Education Department of Gansu Province(2022A-041)the open foundation of Xinjiang Key Laboratory of Water Cycle and Utilization in Arid Zone(XJYS0907-2023-01).
文摘The Qilian Mountains(QM)possess a delicate vegetation ecosystem,amplifying the evident response of vegetation phenology to climate change.The relationship between changes in vegetation growth and climate remains complex.To this end,we used MODIS NDVI data to extract the phenological parameters of the vegetation including meadow(MDW),grassland(GSD),and alpine vegetation(ALV))in the QM from 2002 to 2021.Then,we employed path analysis to reveal the direct and indirect impacts of seasonal climate change on vegetation phenology.Additionally,we decomposed the vegetation phenology in a time series using the trigonometric seasonality,Box-Cox transformation,ARMA errors,and Trend Seasonal components model(TBATS).The findings showed a distinct pattern in the vegetation phenology of the QM,characterized by a progressive shift towards an earlier start of the growing season(SOS),a delayed end of the growing season(EOS),and an extended length of the growing season(LOS).The growth cycle of MDW,GSD,and ALV in the QM species is clearly defined.The SOS for MDW and GSD occurred earlier,mainly between late April and August,while the SOS for ALVs occurred between mid-May and mid-August,a one-month delay compared to the other vegetation.The EOS in MDW and GSD were concentrated between late August and April and early September and early January,respectively.Vegetation phenology exhibits distinct responses to seasonal temperature and precipitation patterns.The advancement and delay of SOS were mainly influenced by the direct effect of spring temperatures and precipitation,which affected 19.59%and 22.17%of the study area,respectively.The advancement and delay of EOS were mainly influenced by the direct effect of fall temperatures and precipitation,which affected 30.18%and 21.17%of the area,respectively.On the contrary,the direct effects of temperature and precipitation in summer and winter on vegetation phenology seem less noticeable and were mainly influenced by indirect effects.The indirect effect of winter precipitation is the main factor affecting the advance or delay of SOS,and the area proportions were 16.29%and 23.42%,respectively.The indirect effects of fall temperatures and precipitation were the main factors affecting the delay and advancement of EOS,respectively,with an area share of 15.80%and 21.60%.This study provides valuable insight into the relationship between vegetation phenology and climate change,which can be of great practical value for the ecological protection of the Qinghai-Tibetan Plateau as well as for the development of GSD ecological animal husbandry in the QM alpine pastoral area.
基金funded by the National Key Research and Development Program of China(Grant No.2022YFF1302903).
文摘The driving effects of climate change and human activities on vegetation change have always been a focal point of research.However,the coupling mechanisms of these driving factors across different temporal and spatial scales remain controversial.The Southwestern Alpine Canyon Region of China(SACR),as an ecologically fragile area,is highly sensitive to the impacts of climate change and human activities.This study constructed a vegetation cover dataset for the SACR based on the Enhanced Vegetation Index(EVI)from 2000 to 2020.Spatial autocorrelation,Theil-Sen trend,and Mann-Kendall tests were used to analyze the spatiotemporal characteristics of vegetation cover changes.The main drivers of spatial heterogeneity in vegetation cover were identified using the optimal parameter geographic detector,and an improved residual analysis model was employed to quantify the relative contributions of climate change and human activities to interannual vegetation cover changes.The main findings are as follows:Spatially,vegetation cover exceeds 60%in most areas,especially in the southern part of the study area.However,the border area between Linzhi and Changdu exhibits lower vegetation cover.Climate factors are the primary drivers of spatial heterogeneity in vegetation cover,with temperature having the most significant influence,as indicated by its q-value,which far exceeds that of other factors.Additionally,the interaction q-value between the two factors significantly increases,showing a relationship of bivariate enhancement and nonlinear enhancement.In terms of temporal changes,vegetation cover shows an overall improving trend from 2000 to 2020,with significant increases observed in 68.93%of the study area.Among these,human activities are the main factors driving vegetation cover change,with a relative contribution rate of 41.31%,while climate change and residual factors contribute 35.66%and 23.53%,respectively.By thoroughly exploring the coupled mechanisms of vegetation change,this study provides important references for the sustainable management and conservation of the vegetation ecosystem in the SACR.
基金funded by the National Key Research and Development Program of China (2023YFC3206803)the National Natural Science Foundation of China (42271493)
文摘Atmospheric deposition of nitrogen(N)plays a significant role in shaping the structure and functioning of various terrestrial ecosystems worldwide.However,the magnitude of N deposition on grassland ecosystems in Central Asia still remains highly uncertain.In this study,a multi-data approach was adopted to analyze the distribution and amplitude of N deposition effects in Central Asia from 1979 to 2014 using a process-based denitrification decomposition(DNDC)model.Results showed that total vegetation carbon(C)in Central Asia was 0.35(±0.09)Pg C/a and the averaged water stress index(WSI)was 0.20(±0.02)for the whole area.Increasing N deposition led to an increase in the vegetation C of 65.56(±83.03)Tg C and slightly decreased water stress in Central Asia.Findings of this study will expand both our understanding and predictive capacity of C characteristics under future increases in N deposition,and also serve as a valuable reference for decision-making regarding water resources management and climate change mitigation in arid and semi-arid areas globally.
基金funded by the Norwegian Research Council through the project MitiStress(Grant No.286773).
文摘Revegetation of former agricultural land is a key option for climate change mitigation and nature conservation.Expansion and abandonment of agricultural land is typically influenced by trends in diets and agricultural inten-sification,which are two key parameters in the Shared Socioeconomic Pathways(SSPs).Datasets mapping future land dynamics under different SSPs and climate change mitigation targets stem from different scenario assump-tions,land data and modelling frameworks.This study aims to determine the role that these three factors play in the estimates of the evolution of cropland and pastureland in future SSPs under different climate scenarios from four main datasets largely used in the climate and land surface studies.The datasets largely agree with the rep-resentation of cropland at present-day conditions,but the identification of pastureland is ambiguous and shows large discrepancies due to the lack of a unique land-use category.Differences occur with future projections,even for the same SSP and climate target.Accounting for CO_(2)sequestration from revegetation of abandoned agri-cultural land and CO_(2)emissions from forest clearance due to agricultural expansion shows a net reduction in vegetation carbon stock for most SSPs considered,except SSP1.However,different datasets give differences in estimates,even when representative of the same scenario.With SSP1,the cumulative increase in carbon stock until 2050 is 3.3 GtC for one dataset,and more than double for another.Our study calls for a common classifica-tion system with improved detection of pastureland to harmonize projections and reduce variability of outcomes in environmental studies.
文摘Changing climate will jeopardize biodiversity,particularly the geographic distribution of endemic species.One such species is the Javan Hawk-Eagle(JHE,Nisaetus bartelsi),a charismatic raptor found only on Java Island,Indonesia.Thus,it is crucial to develop an appropriate conservation strategy to preserve the species.Ecological niche modeling is considered a valuable tool for designing conservation plans for the JHE.We provide an ecological niche modeling approach and transfer its model to future climate scenarios for the JHE.We utilize various machine learning algorithms under sustainability and business-as-usual(BAU)scenarios for 2050.Additionally,we investigate the conservation vulnerability of the JHE,capturing multifaceted pressures on the species from climate dissimilarities and human disturbance variables.Our study reveals that the ensemble model performs exceptionally well,with temperature emerging as the most critical factor affecting the JHE distribution.This finding indicates that climate change will have a significant impact on the JHE species.Our results suggest that the JHE distribution will likely decrease by 28.41%and 40.16%from the current JHE distribution under sustainability and BAU scenarios,respectively.Furthermore,our study reveals high-potential refugia for future JHE,covering 7,596 km^(2)(61%)under the sustainability scenario and only 4,403 km^(2)(35%)under the BAU scenario.Therefore,effective management and planning,including habitat restoration,refugia preservation,habitat connectivity,and local community inclusivity,should be well-managed to achieve JHE conservation targets.
基金The work was partially supported by research project funding from the Undergraduate Research Grant,Arkansas Tech University.
文摘Quercus arkansana(Arkansas oak)is at risk of becoming endangered,as the total known population size is represented by a few isolated populations.The potential impact of climate change on this species in the near future is high,yet knowledge of its predicted effects is limited.Our study utilized the biomod2 R package to develop habi-tat suitability ensemble models based on bioclimatic and topographic environmental variables and the known loca-tions of current distribution of Q.arkansana.We predicted suitable habitats across three climate change scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5)for 2050,2070,and 2090.Our findings reveal that the current suitable habitat for Q.arkansana is approximately 127,881 km^(2) across seven states(Texas,Arkansas,Alabama,Louisiana,Mississippi,Georgia,and Florida);approximately 9.5%is encompassed within state and federally managed protected areas.Our models predict that all current suitable habitats will disap-pear by 2050 due to climate change,resulting in a northward shift into new regions such as Tennessee and Kentucky.The large extent of suitable habitat outside protected areas sug-gests that a species-specific action plan incorporating pro-tected areas and other areas may be crucial for its conserva-tion.Moreover,protection of Q.arkansana habitat against climate change may require locally and regionally focused conservation policies,adaptive management strategies,and educational outreach among local people.