Local Climate Change Induced by Urbanization on a South China Sea Island

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.

Habitable Land Will Soon Become the World’s Scarcest Resource: Why Appalachia Should Choose Climate Change Havens over Millionaire Estates and Golf Courses

This research advocates for the construction of Climate Change Haven Communities across the Appalachian Region. The proposed development plan can be extended to the northern tier states across the US and also to the northern and mountainous regions of Europe and Asia. We present an analogy to the earlier climate change period of the Last Glacial Maximum/“Ice Age” in which these same northern regions of the planet were covered in ice sheets making them uninhabitable for most humans and many plant and animal species. In some significant ways, the Ice Age scenario can be a reverse-model for our current climate crisis. We also advocate strongly for the prevention of upscale real estate development projects in these same regions of the globe, as these will foreclose the possibility of safely sheltering the millions of persons who will be displaced by climate change over the next 5 to 10 years.

Spatiotemporal changes of gross primary productivity and its response to drought in the Mongolian Plateau under climate change

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.

A study on the simulation of carbon and water fluxes of Dangxiong alpine meadow and its response to climate change

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.

Climate change drives flooding risk increases in the Yellow River Basin

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.

Prevalence of vegetation browning in China’s drylands under climate change

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.

Differential response of radial growth and δ^(13)C in Qinghai spruce(Picea crassifolia) to climate change on the southern and northern slopes of the Qilian Mountains in Northwest China

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.

Quantitative contributions of climate change and human activities to vegetation dynamics in the Zoige Plateau from 2001 to 2020

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.

Potential distribution of Haloxylon ammodendron in Central Asia under climate change

Understanding the spatial distribution of plant species and their dynamic changes in arid areas is crucial for addressing the challenges posed by climate change.Haloxylon ammodendron shelterbelts are essential for the protection of plant resources and the control of desertification in Central Asia.Thus far,the potential suitable habitats of H.ammodendron in Central Asia are still uncertain in the future under global climate change conditions.This study utilised the maximum entropy(MaxEnt)model to combine the current distribution data of H.ammodendron with its growth-related data to analyze the potential distribution pattern of H.ammodendron across Central Asia.The results show that there are suitable habitats of H.ammodendron in the Aralkum Desert,northern slopes of the Tianshan Mountains,and the upstream of the Tarim River and western edge of the Taklimakan Desert in the Tarim Basin under the current climate conditions.The period from 2021 to 2040 is projected to undergo significant changes in the suitable habitat area of H.ammodendron in Central Asia,with a projected 15.0% decrease in the unsuitable habitat area.Inland areas farther from the ocean,such as the Caspian Sea and Aralkum Desert,will continue to experience a decrease in the suitable habitats of H.ammodendron.Regions exhibiting frequent fluctuations in the habitat suitability levels are primarily found along the axis stretching from Astana to Kazakhskiy Melkosopochnik in Kazakhstan.These regions can transition into suitable habitats under varying climate conditions,requiring the implementation of appropriate human intervention measures to prevent desertification.Future climate conditions are expected to cause an eastward shift in the geometric centre of the potential suitable habitats of H.ammodendron,with the extent of this shift amplifying alongside more greenhouse gas emissions.This study can provide theoretical support for the spatial configuration of H.ammodendron shelterbelts and desertification control in Central Asia,emphasising the importance of proactive measures to adapt to climate change in the future.

Potential reduction in carbon fixation capacity under climate change in a Pinus koraiensis forest

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.

Projected impacts of climate change on the habitat of Xerophyta species in Africa

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.

Prediction of the potential distribution and analysis of the freezing injury risk of winter wheat on the Loess Plateau under climate change

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.

Impacts of climate change and human activities on vegetation dynamics on the Mongolian Plateau, East Asia from 2000 to 2023

The Mongolian Plateau in East Asia is one of the largest contingent arid and semi-arid areas of the world.Under the impacts of climate change and human activities,desertification is becoming increasingly severe on the Mongolian Plateau.Understanding the vegetation dynamics in this region can better characterize its ecological changes.In this study,based on Moderate Resolution Imaging Spectroradiometer(MODIS)images,we calculated the kernel normalized difference vegetation index(kNDVI)on the Mongolian Plateau from 2000 to 2023,and analyzed the changes in kNDVI using the Theil-Sen median trend analysis and Mann-Kendall significance test.We further investigated the impact of climate change on kNDVI change using partial correlation analysis and composite correlation analysis,and quantified the effects of climate change and human activities on kNDVI change by residual analysis.The results showed that kNDVI on the Mongolian Plateau was increasing overall,and the vegetation recovery area in the southern region was significantly larger than that in the northern region.About 50.99%of the plateau showed dominant climate-driven effects of temperature,precipitation,and wind speed on kNDVI change.Residual analysis showed that climate change and human activities together contributed to 94.79%of the areas with vegetation improvement.Appropriate human activities promoted the recovery of local vegetation,and climate change inhibited vegetation growth in the northern part of the Mongolian Plateau.This study provides scientific data for understanding the regional ecological environment status and future changes and developing effective ecological protection measures on the Mongolian Plateau.

Effects of nitrogen deposition on the carbon budget and water stress in Central Asia under climate change

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.

Coupled effects of climate change and human activities on vegetation dynamics in the Southwestern Alpine Canyon Region of China

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.

Response of vegetation variation to climate change and human activities in the Shiyang River Basin of China during 2001-2022

Understanding the response of vegetation variation to climate change and human activities is critical for addressing future conflicts between humans and the environment,and maintaining ecosystem stability.Here,we aimed to identify the determining factors of vegetation variation and explore the sensitivity of vegetation to temperature(SVT)and the sensitivity of vegetation to precipitation(SVP)in the Shiyang River Basin(SYRB)of China during 2001-2022.The climate data from climatic research unit(CRU),vegetation index data from Moderate Resolution Imaging Spectroradiometer(MODIS),and land use data from Landsat images were used to analyze the spatial-temporal changes in vegetation indices,climate,and land use in the SYRB and its sub-basins(i.e.,upstream,midstream,and downstream basins)during 2001-2022.Linear regression analysis and correlation analysis were used to explore the SVT and SVP,revealing the driving factors of vegetation variation.Significant increasing trends(P<0.05)were detected for the enhanced vegetation index(EVI)and normalized difference vegetation index(NDVI)in the SYRB during 2001-2022,with most regions(84%)experiencing significant variation in vegetation,and land use change was determined as the dominant factor of vegetation variation.Non-significant decreasing trends were detected in the SVT and SVP of the SYRB during 2001-2022.There were spatial differences in vegetation variation,SVT,and SVP.Although NDVI and EVI exhibited increasing trends in the upstream,midstream,and downstream basins,the change slope in the downstream basin was lower than those in the upstream and midstream basins,the SVT in the upstream basin was higher than those in the midstream and downstream basins,and the SVP in the downstream basin was lower than those in the upstream and midstream basins.Temperature and precipitation changes controlled vegetation variation in the upstream and midstream basins while human activities(land use change)dominated vegetation variation in the downstream basin.We concluded that there is a spatial heterogeneity in the response of vegetation variation to climate change and human activities across different sub-basins of the SYRB.These findings can enhance our understanding of the relationship among vegetation variation,climate change,and human activities,and provide a reference for addressing future conflicts between humans and the environment in the arid inland river basins.

Impact of climate change and human activities on the spatiotemporal dynamics of surface water area in Gansu Province, China

Understanding the dynamics of surface water area and their drivers is crucial for human survival and ecosystem stability in inland arid and semi-arid areas.This study took Gansu Province,China,a typical area with complex terrain and variable climate,as the research subject.Based on Google Earth Engine,we used Landsat data and the Open-surface Water Detection Method with Enhanced Impurity Control method to monitor the spatiotemporal dynamics of surface water area in Gansu Province from 1985 to 2022,and quantitatively analyzed the main causes of regional differences in surface water area.The findings revealed that surface water area in Gansu Province expanded by 406.88 km2 from 1985 to 2022.Seasonal surface water area exhibited significant fluctuations,while permanent surface water area showed a steady increase.Notably,terrestrial water storage exhibited a trend of first decreasing and then increasing,correlated with the dynamics of surface water area.Climate change and human activities jointly affected surface hydrological processes,with the impact of climate change being slightly higher than that of human activities.Spatially,climate change affected the'source'of surface water to a greater extent,while human activities tended to affect the'destination'of surface water.Challenges of surface water resources faced by inland arid and semi-arid areas like Gansu Province are multifaceted.Therefore,we summarized the surface hydrology patterns typical in inland arid and semi-arid areas and tailored surface water'supply-demand'balance strategies.The study not only sheds light on the dynamics of surface water area in Gansu Province,but also offers valuable insights for ecological protection and surface water resource management in inland arid and semi-arid areas facing water scarcity.

Phenology of different types of vegetation and their response to climate change in the Qilian Mountains,China

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.

Comparative Assessment of Impacts of Future Climate Change on Runoff in Upper Daqinghe Basin,China

Assessing runoff changes is of great importance especially its responses to the projected future climate change on local scale basins because such analyses are generally done on global and regional scales which may lead to generalized conclusions rather than specific ones.Climate change affected the runoff variation in the past in the upper Daqinghe Basin,however,the climate was mainly considered uncertain and still needs further studies,especially its future impacts on runoff for better water resources management and planning.Integrated with a set of climate simulations,a daily conceptual hydrological model(MIKE11-NAM)was applied to assess the impact of climate change on runoff conditions in the Daomaguan,Fuping and Zijingguan basins in the upper Daqinghe Basin.Historical hydrological data(2008–2017)were used to evaluate the applicability of the MIKE11-NAM model.After bias correction,future projected climate change and its impacts on runoff(2025–2054)were analysed and compared to the baseline period(1985–2014)under three shared social economic pathways(SSP1-2.6,SSP2-4.5,and SSP5-8.5)scenarios from Coupled Model Intercomparison Project Phase 6(CMIP6)simulations.The MIKE-11 NAM model was applicable in all three Basins,with both R^(2)and Nash-Sutcliffe Efficiency coefficients greater than 0.6 at daily scale for both calibration(2009–2011)and validation(2012–2017)periods,respectively.Although uncertainties remain,temperature and precipitation are projected to increase compared to the baseline where higher increases in precipitation and temperature are projected to occur under SSP2-4.5 and SSP5-8.5 scenarios,respectively in all the basins.Precipitation changes will range between 12%–19%whereas temperature change will be 2.0℃–2.5℃ under the SSP2-4.5 and SSP5-8.5 scenarios,respectively.In addition,higher warming is projected to occur in colder months than in warmer months.Overall,the runoff of these three basins is projected to respond to projected climate changes differently because runoff is projected to only increase in the Fuping basin under SSP2-4.5 whereas decreases in both Daomaguan and Zijingguan Basins under all scenarios.This study’s findings could be important when setting mitigation strategies for climate change and water resources management.

A CMIP6-based assessment of regional climate change in the Chinese Tianshan Mountains

Climate warming profoundly affects hydrological changes,agricultural production,and human society.Arid and semi-arid areas of China are currently displaying a marked trend of warming and wetting.The Chinese Tianshan Mountains(CTM)have a high climate sensitivity,rendering the region particularly vulnerable to the effects of climate warming.In this study,we used monthly average temperature and monthly precipitation data from the CN05.1 gridded dataset(1961-2014)and 24 global climate models(GCMs)of the Coupled Model Intercomparison Project Phase 6(CMIP6)to assess the applicability of the CMIP6 GCMs in the CTM at the regional scale.Based on this,we conducted a systematic review of the interannual trends,dry-wet transitions(based on the standardized precipitation index(SPI)),and spatial distribution patterns of climate change in the CTM during 1961-2014.We further projected future temperature and precipitation changes over three terms(near-term(2021-2040),mid-term(2041-2060),and long-term(2081-2100))relative to the historical period(1961-2014)under four shared socio-economic pathway(SSP)scenarios(i.e.,SSP1-2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5).It was found that the CTM had experienced significant warming and wetting from 1961 to 2014,and will also experience warming in the future(2021-2100).Substantial warming in 1997 was captured by both the CN05.1 derived from interpolating meteorological station data and the multi-model ensemble(MME)from the CMIP6 GCMs.The MME simulation results indicated an apparent wetting in 2008,which occurred later than the wetting observed from the CN05.1 in 1989.The GCMs generally underestimated spring temperature and overestimated both winter temperature and spring precipitation in the CTM.Warming and wetting are more rapid in the northern part of the CTM.By the end of the 21st century,all the four SSP scenarios project warmer and wetter conditions in the CTM with multiple dry-wet transitions.However,the rise in precipitation fails to counterbalance the drought induced by escalating temperature in the future,so the nature of the drought in the CTM will not change at all.Additionally,the projected summer precipitation shows negative correlation with the radiative forcing.This study holds practical implications for the awareness of climate change and subsequent research in the CTM.