Native grasslands in the Pampas of South America are increasingly being replaced by Eucalyptus and Pinus stands.The short rotation regimes used for the stands require high nutrient levels,with litterfall being a major...Native grasslands in the Pampas of South America are increasingly being replaced by Eucalyptus and Pinus stands.The short rotation regimes used for the stands require high nutrient levels,with litterfall being a major source of nutrient return.To model the litterfall production using climatic variables and assess the nutrient return in 14-year-old Eucalyptus grandis and Pinus taeda stands,we measured litter production over 2 years,using conical litter traps,and monitored climatic variables.Mean temperature,accumulated precipitation,and mean maximum vapor pres-sure deficit at the seasonal level influenced litterfall produc-tion by E.grandis;seasonal accumulated precipitation and mean maximum temperature affected litterfall by P.taeda.The regression tree modeling based on these climatic vari-ables had great accuracy and predictive power for E.grandis(N=33;MAE(mean absolute error)=0.65;RMSE(root mean square error)=0.91;R^(2)=0.71)and P.taeda(N=108;MAE=1.50;RMSE=1.59;R^(2)=0.72).The nutrient return followed a similar pattern to litterfall deposition,as well as the order of importance of macronutrients(E.grandis:Ca>N>K>Mg>P;P.taeda:N>Ca>K>Mg>P)and micronutrients(E.grandis and P.taeda:Mn>Fe>Zn>Cu)in both species.This study constitutes a first approximation of factors that affect litterfall and nutrient return in these systems.展开更多
Latewood width(LWW)indices of trees are considered a reliable proxy of summer precipitation in the Northern Hemisphere.However,the strong coupling and high correlation between earlywood width(EWW)and LWW indices often...Latewood width(LWW)indices of trees are considered a reliable proxy of summer precipitation in the Northern Hemisphere.However,the strong coupling and high correlation between earlywood width(EWW)and LWW indices often prevent registration of climate signals of the LWW index.In this study,328-year-long earlywood width and latewood width chronologies were developed from Chinese pine at two sites in the Hasi Mountains,north central China.The climate responses of these chronologies were analyzed and the LWW index used to derive sum-mer precipitation signals.Correlation analyses showed that LWW was particularly influenced by earlywood growth and recorded stronger climate signals of the previous year as EWW,rather than those of the current year with infrequent summer climate signals.However,after removing the effect of earlywood growth using a simple regression model,the adjusted LWW chronology(LWW_(adj))showed a strong relationship with July precipitation in dry years.This suggests that the LWW_(adj) chronology has the potential to be used to investigate long-term variability in summer precipitation in drought-limited regions.展开更多
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
Smallholder farmers in Ahafo Ano North District,Ghana,face multiple climatic and non-climatic issues.This study assessed the factors contributing to the livelihood vulnerability of smallholder farmers in this district...Smallholder farmers in Ahafo Ano North District,Ghana,face multiple climatic and non-climatic issues.This study assessed the factors contributing to the livelihood vulnerability of smallholder farmers in this district by household surveys with 200 respondents and focus group discussions(FGDs)with 10 respondents.The Mann–Kendall trend test was used to assess mean annual rainfall and temperature trends from 2002 to 2022.The relative importance index(RII)value was used to rank the climatic and non-climatic factors perceived by respondents.The socioeconomic characteristics affecting smallholder farmers’perceptions of climatic and non-climatic factors were evaluated by the binary logistic regression model.Results showed that mean annual rainfall decreased(P>0.05)but mean annual temperature significantly increased(P<0.05)from 2002 to 2022 in the district.The key climatic factors perceived by smallholder farmers were extreme heat or increasing temperature(RII=0.498),erratic rainfall(RII=0.485),and increased windstorms(RII=0.475).The critical non-climatic factors were high cost of farm inputs(RII=0.485),high cost of healthcare(RII=0.435),and poor condition of roads to farms(RII=0.415).Smallholder farmers’perceptions of climatic and non-climatic factors were significantly affected by their socioeconomic characteristics(P<0.05).This study concluded that these factors negatively impact the livelihoods and well-being of smallholder farmers and socioeconomic characteristics influence their perceptions of these factors.Therefore,to enhance the resilience of smallholder farmers to climate change,it is necessary to adopt a comprehensive and context-specific approach that accounts for climatic and non-climatic factors.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
Based on the daily meteorological observation data of seven meteorological stations in southern Tibet from 1980 to 2021 (April-October), the temporal and spatial variation characteristics and influencing factors of ar...Based on the daily meteorological observation data of seven meteorological stations in southern Tibet from 1980 to 2021 (April-October), the temporal and spatial variation characteristics and influencing factors of aridity index ( AI ) in the growing season of major grain producing areas in Tibet were studied by using climate tendency rate, Mann-Kendal test, Morlet wavelet analysis, GIS hybrid interpolation method, Pearson correlation coefficient, contribution rate analysis and other methods. The results showed that the average AI in the main grain producing areas of Tibet was 1.7, which belonged to the semi-arid area, and the overall trend was decreasing (humidifying) (-0.036/10 a). The linear decreasing trend was different in different regions, and the area around Lhatse County was the most significant (-0.26/10 a). AI had no obvious abrupt change, and had long- and medium-term fluctuation characteristics of 24 years, 6 years. The spatial distribution was uneven, and had the characteristics of ‘shrinking arid area and expanding humid area . The contribution rates of the main climate influencing factors of AI varied in different regions. In general, the contribution rates after quantification was as follows: precipitation (34.9%)>relative humidity (28.4%)>sunshine (19.9%)>maximum temperature (12.4%).展开更多
This study aims to assess the synergies and trade-offs of regulating ecosystem services. Ecosystem services are non-linearly interconnected and changes in one service can positively or negatively affect another. We ev...This study aims to assess the synergies and trade-offs of regulating ecosystem services. Ecosystem services are non-linearly interconnected and changes in one service can positively or negatively affect another. We evaluated ecosystem services based on biophysical indicators using an expert scoring system that determines the corresponding soil functions and is part of the existing databases available in Slovakia. This methodological combination enabled us to provide unique mapping and assessment of ecosystem services within Slovakia. Correlation analysis between individual regulating ecosystem services and climate regions, slope, texture, and altitude confirm the statistically significant influence of climate and slope in all agricultural land, arable land, and grassland ecosystems. Statistically significant synergistic effects were established between the regulation of the water regime and the regulation of soil erosion within each climate region, apart from the very warm climate region. Only in a very warm climate region was potential of regulating ecosystem services mutually beneficial for soil erosion control and soil cleaning potential (immobilization of inorganic pollutants).展开更多
Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model o...Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in<sup>2</sup>/s for humidity, 2.993 in<sup>2</sup>/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .展开更多
Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of ...Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of physics in climate science has occasionally been overlooked.Our perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”scenario.Scrutinizing controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical constraints.Furthermore,we provide illustrative examples to guide future assessments and constraints for AI models.Regarding AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online schemes.Additionally,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)principles.Through a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal.展开更多
The global physical and biogeochemical environment has been substantially altered in response to increased atmospheric greenhouse gases from human activities.In 2023,the sea surface temperature(SST)and upper 2000 m oc...The global physical and biogeochemical environment has been substantially altered in response to increased atmospheric greenhouse gases from human activities.In 2023,the sea surface temperature(SST)and upper 2000 m ocean heat content(OHC)reached record highs.The 0–2000 m OHC in 2023 exceeded that of 2022 by 15±10 ZJ(1 Zetta Joules=1021 Joules)(updated IAP/CAS data);9±5 ZJ(NCEI/NOAA data).The Tropical Atlantic Ocean,the Mediterranean Sea,and southern oceans recorded their highest OHC observed since the 1950s.Associated with the onset of a strong El Niño,the global SST reached its record high in 2023 with an annual mean of~0.23℃ higher than 2022 and an astounding>0.3℃ above 2022 values for the second half of 2023.The density stratification and spatial temperature inhomogeneity indexes reached their highest values in 2023.展开更多
In the Sahel region, the population depends largely on rain-fed agriculture. In West Africa in particular, climate models turn out to be unable to capture some basic features of present-day climate variability. This s...In the Sahel region, the population depends largely on rain-fed agriculture. In West Africa in particular, climate models turn out to be unable to capture some basic features of present-day climate variability. This study proposes a contribution to the analysis of the evolution of agro-climatic risks in the context of climate variability. Some statistical tests are used on the main variables of the rainy season to determine the trends and the variabilities described by the data series. Thus, the paper provides a statistical modeling of the different agro-climatic risks while the seasonal variability of agro-climatic parameters was analyzed as well as their inter annual variability. The study identifies the probability distributions of agroclimatic risks and the characterization of the rainy season was clarified.展开更多
Dear colleagues,We would like to invite you to participate in the special issue of the journal Advances in Polar Science(ISSN 1674-9928)entitled“Past and Present Climatic Change in Antarctica:Geological Proxies and B...Dear colleagues,We would like to invite you to participate in the special issue of the journal Advances in Polar Science(ISSN 1674-9928)entitled“Past and Present Climatic Change in Antarctica:Geological Proxies and Biological Processes”,which is expected to be published in March 2024 as general issue(Vol.35,No.1).We are honored to invite Dra.Carolina Acosta Hospitaleche,Dr.Javier N.Gelfo,Dr.Marcelo Reguero,Dra.Adolfina Savoretti and Dra.展开更多
Precipitation projections over the Tibetan Plateau(TP)show diversity among existing studies,partly due to model uncertainty.How to develop a reliable projection remains inconclusive.Here,based on the IPCC AR6–assesse...Precipitation projections over the Tibetan Plateau(TP)show diversity among existing studies,partly due to model uncertainty.How to develop a reliable projection remains inconclusive.Here,based on the IPCC AR6–assessed likely range of equilibrium climate sensitivity(ECS)and the climatological precipitation performance,the authors constrain the CMIP6(phase 6 of the Coupled Model Intercomparison Project)model projection of summer precipitation and water availability over the TP.The best estimates of precipitation changes are 0.24,0.25,and 0.45 mm d^(−1)(5.9%,6.1%,and 11.2%)under the Shared Socioeconomic Pathway(SSP)scenarios of SSP1–2.6,SSP2–4.5,and SSP5–8.5 from 2050–2099 relative to 1965–2014,respectively.The corresponding constrained projections of water availability measured by precipitation minus evaporation(P–E)are 0.10,0.09,and 0.22 mm d^(−1)(5.7%,4.9%,and 13.2%),respectively.The increase of precipitation and P–E projected by the high-ECS models,whose ECS values are higher than the upper limit of the likely range,are about 1.7 times larger than those estimated by constrained projections.Spatially,there is a larger increase in precipitation and P–E over the eastern TP,while the western part shows a relatively weak difference in precipitation and a drier trend in P–E.The wetter TP projected by the high-ECS models resulted from both an approximately 1.2–1.4 times stronger hydrological sensitivity and additional warming of 0.6℃–1.2℃ under all three scenarios during 2050–2099.This study emphasizes that selecting climate models with climate sensitivity within the likely range is crucial to reducing the uncertainty in the projection of TP precipitation and water availability changes.展开更多
A set of standard chronologies for tree-ring width(TRW),earlywood width(EWW)and latewood width(LWW)in Pinus tabuliformis Carr.along an altitudi-nal gradient(1450,1400,and 1350 m a.s.l.)on Baiyunshan Mountain,Central C...A set of standard chronologies for tree-ring width(TRW),earlywood width(EWW)and latewood width(LWW)in Pinus tabuliformis Carr.along an altitudi-nal gradient(1450,1400,and 1350 m a.s.l.)on Baiyunshan Mountain,Central China to analyze the effect of varying temperature and precipitation on growth along the gradi-ent.Correlation analyses showed that at all three altitudes and the TRW and EWW chronologies generally had signifi-cant negative correlations with mean and maximum tem-peratures in the current April and May and with minimum temperatures in the prior July and August,but significant positive correlations with precipitation in the current May.Correlations were generally significantly negative between LWW chronologies and all temperatures in the prior July and August,indicating that the prior summer temperature had a strong lag effect on the growth of P.tabuliformis that increased with altitude.The correlation with the standard-ized precipitation evapotranspiration index(SPEI)confirmed that wet conditions in the current May promoted growth of TR and EW at all altitudes.Significant altitudinal differences were also found;at 1400 m,there were significant positive correlations between EWW chronologies and SPEI in the current April and significant negative correlations between LWW chronologies and SPEI in the current September,but these correlations were not significant at 1450 m.At 1350 m,there were also significant negative correlations between the TRW and the EWW chronologies and SPEI in the prior October and the current July and between LWW chronology and SPEI in the current August,but these cor-relations were not significant at 1400 m.Moving correlation results showed a stable response of EWW in relation to the SPEI in the current May at all three altitudes and of LWW to maximum temperature in the prior July-August at 1400 m from 2002 to 2018.The EWW chronology at 1400 m and the LWW chronology at 1450 m were identified as more suitable for climate reconstruction.These results provide a strong scientific basis for forest management decisions and climate reconstructions in Central China.展开更多
Like other countries in East Africa, Tanzania has been affected by extreme precipitation incidences both socially and economically. Determining the trend and variability features of extreme precipitation in the countr...Like other countries in East Africa, Tanzania has been affected by extreme precipitation incidences both socially and economically. Determining the trend and variability features of extreme precipitation in the country is crucial. This study used data from 28 meteorological stations for 1981-2020 period to give an annual and seasonal analysis of the patterns of 10 ETCCDI’s extreme precipitation indices over the regions. At annual scale, the results showed that increasing trends had high frequency percentage than the decreasing ones, collecting about 76% in total. The decreasing trend was approximately 24%, and most of the stations with increasing percentage in trend are concentrated in Northern coast, Central, West, North-eastern highlands and Lake Victoria Basin. Most of the stations depicted negative trend are concentrated over Southern region. This highlights that extreme precipitation events have increased over the country for the period 1981-2020. At seasonal scale, during October to December (OND);the patterns of extreme precipitation climatic indices except R99p, showed positive significant increasing trend over Lake Victoria Basin and some Western parts of the country. In general, spatial patterns indicate decrease of precipitation over most parts of the country during OND. The seasonal average time series depicted non-significant positive trend during March to April (MAM) season, except for Consecutive Wet Days (CWD) which showed non-significant decreasing trend. Over the highest mountain in Africa, Kilimanjaro;the study has revealed significant decrease in Annual total-wet Precipitation (PRCPTOT), the number of heavy (very heavy) days of precipitation R10 mm (R20 mm) and Consecutive Wet Days (CWD) during MAM season. While the maximum one-day precipitation amount (RX1 day) was observed to decrease significantly over the Mountain during OND season. The result is very important in risk assessment and preparedness perspective in planning climate change mitigation and adaptations for different sectors like Tourism, Agriculture, Water and Energy.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 rapid warming of the Arctic,accompanied by glacier and sea ice melt,has significant consequences for the Earth’s climate,ecosystems,and economy.Black carbon(BC)deposition on snow and ice can trigger a significant...The rapid warming of the Arctic,accompanied by glacier and sea ice melt,has significant consequences for the Earth’s climate,ecosystems,and economy.Black carbon(BC)deposition on snow and ice can trigger a significant reduction in snow albedo and accelerate melting of snow and ice in the Arctic.By reviewing the published literatures over the past decades,this work provides an overview of the progress in both the measurement and modeling of BC deposition and its impact on Arctic climate change.In summary,the maximum value of BC deposition appears in the western Russian Arctic(26 ng·g^(–1)),and the minimum value appears in Greenland(3 ng·g^(–1)).BC records in the Arctic ice core already peaked in 1920s and 1970s,and shows a regional difference between Greenland and Canadian Arctic.The different temporal variations of Arctic BC ice core records in different regions are closely related to the large variability of BC emissions and transportation processes across the Arctic region.Model simulations usually underestimate the concentration of BC in snow and ice by 2–3 times,and cannot accurately reflect the seasonal and regional changes in BC deposition.Wet deposition is the main removal mechanism of BC in the Arctic,and observations show different seasonal variations in BC wet deposition in Ny-Ålesund and Barrow.This discrepancy may result from varying contributions of anthropogenic and biomass burning(BB)emissions,given the strong influence by BC from BB emissions at Barrow.Arctic BC deposition significantly influences regional climate change in the Arctic,increasing fire activities in the Arctic have made BB source of Arctic BC more crucial.On average,BC in Arctic snow and ice causes an increase of+0.17 W·m^(–2)in radiative forcing and 8 Gt·a^(–1)in runoff in Greenland.As stressed in the latest Arctic Monitoring and Assessment Programme report,reliable source information and long-term and high-resolution observations on Arctic BC deposition will be crucial for a more comprehensive understanding and a better mitigation strategy of Arctic BC.In the future,it is necessary to collect more observations on BC deposition and the corresponding physical processes(e.g.,snow/ice melting,surface energy balance)in the Arctic to provide reliable data for understanding and clarifying the mechanism of the climatic impacts of BC deposition on Arctic snow and ice.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
Tsutsusi is one of the eight subgenera of the Rhododendron genus.Four Tsutsusi species,R.indicum,R.simisii,R.oldhamii,and R.schlippenbachii,have high ornamental and medicinal values,resulting in an increasing market d...Tsutsusi is one of the eight subgenera of the Rhododendron genus.Four Tsutsusi species,R.indicum,R.simisii,R.oldhamii,and R.schlippenbachii,have high ornamental and medicinal values,resulting in an increasing market demand.These species thrive in cool and humid environments and are widely distributed in Europe and Asia.Whether global climate warming will affect the distribution of these valuable resources remains unclear.Thus,this study analyzed the climatic suitability of these species for the first time on the basis of 1552 geographical distribution points and 19 bioclimatic factors using the maximum entropy model.The results show that a suitable distribution area for all four species would decrease under climate warming.The main bioclimatic factors affecting their distribution are the mean temperature of the coldest quarter for R.indicum,the mean diurnal range for R.simisii,and precipitation of the warmest quarter for R.oldhamii and R.schlippenbachii.In addition,the contribution of the temperature-related bioclimatic factors to the distribution of R.indicum and R.simisii is higher than that of the associated precipitation-related climatic factors;in contrast,the contribution of precipitation-related bioclimatic factors to the distribution of R.oldhamii and R.schlippenbachii is higher than that of the temperature-related climatic factors.These results provide references for the introduction,conservation,sustainable development,and utilization of these four species in the future,and may also provide information with regards to other Rhododendron species.展开更多
基金funded by Lumin S.A. and the Agencia Nacional de Investigación e Innovación (ANII)[POS_NAC_2016_1_130479]
文摘Native grasslands in the Pampas of South America are increasingly being replaced by Eucalyptus and Pinus stands.The short rotation regimes used for the stands require high nutrient levels,with litterfall being a major source of nutrient return.To model the litterfall production using climatic variables and assess the nutrient return in 14-year-old Eucalyptus grandis and Pinus taeda stands,we measured litter production over 2 years,using conical litter traps,and monitored climatic variables.Mean temperature,accumulated precipitation,and mean maximum vapor pres-sure deficit at the seasonal level influenced litterfall produc-tion by E.grandis;seasonal accumulated precipitation and mean maximum temperature affected litterfall by P.taeda.The regression tree modeling based on these climatic vari-ables had great accuracy and predictive power for E.grandis(N=33;MAE(mean absolute error)=0.65;RMSE(root mean square error)=0.91;R^(2)=0.71)and P.taeda(N=108;MAE=1.50;RMSE=1.59;R^(2)=0.72).The nutrient return followed a similar pattern to litterfall deposition,as well as the order of importance of macronutrients(E.grandis:Ca>N>K>Mg>P;P.taeda:N>Ca>K>Mg>P)and micronutrients(E.grandis and P.taeda:Mn>Fe>Zn>Cu)in both species.This study constitutes a first approximation of factors that affect litterfall and nutrient return in these systems.
基金supportedbytheNational Natural Science Foundation of China (No.U21A2006 and 42001043).
文摘Latewood width(LWW)indices of trees are considered a reliable proxy of summer precipitation in the Northern Hemisphere.However,the strong coupling and high correlation between earlywood width(EWW)and LWW indices often prevent registration of climate signals of the LWW index.In this study,328-year-long earlywood width and latewood width chronologies were developed from Chinese pine at two sites in the Hasi Mountains,north central China.The climate responses of these chronologies were analyzed and the LWW index used to derive sum-mer precipitation signals.Correlation analyses showed that LWW was particularly influenced by earlywood growth and recorded stronger climate signals of the previous year as EWW,rather than those of the current year with infrequent summer climate signals.However,after removing the effect of earlywood growth using a simple regression model,the adjusted LWW chronology(LWW_(adj))showed a strong relationship with July precipitation in dry years.This suggests that the LWW_(adj) chronology has the potential to be used to investigate long-term variability in summer precipitation in drought-limited regions.
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Smallholder farmers in Ahafo Ano North District,Ghana,face multiple climatic and non-climatic issues.This study assessed the factors contributing to the livelihood vulnerability of smallholder farmers in this district by household surveys with 200 respondents and focus group discussions(FGDs)with 10 respondents.The Mann–Kendall trend test was used to assess mean annual rainfall and temperature trends from 2002 to 2022.The relative importance index(RII)value was used to rank the climatic and non-climatic factors perceived by respondents.The socioeconomic characteristics affecting smallholder farmers’perceptions of climatic and non-climatic factors were evaluated by the binary logistic regression model.Results showed that mean annual rainfall decreased(P>0.05)but mean annual temperature significantly increased(P<0.05)from 2002 to 2022 in the district.The key climatic factors perceived by smallholder farmers were extreme heat or increasing temperature(RII=0.498),erratic rainfall(RII=0.485),and increased windstorms(RII=0.475).The critical non-climatic factors were high cost of farm inputs(RII=0.485),high cost of healthcare(RII=0.435),and poor condition of roads to farms(RII=0.415).Smallholder farmers’perceptions of climatic and non-climatic factors were significantly affected by their socioeconomic characteristics(P<0.05).This study concluded that these factors negatively impact the livelihoods and well-being of smallholder farmers and socioeconomic characteristics influence their perceptions of these factors.Therefore,to enhance the resilience of smallholder farmers to climate change,it is necessary to adopt a comprehensive and context-specific approach that accounts for climatic and non-climatic factors.
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Supported by Natural Science Foundation of Tibet Autonomous Region(XZ202001ZR0082G)National Key Research and Development Program of China(2020YFA0608203)Key Research and Development of Science and Technology Program of Tibet Autonomous Region(CGZH2024000002)。
文摘Based on the daily meteorological observation data of seven meteorological stations in southern Tibet from 1980 to 2021 (April-October), the temporal and spatial variation characteristics and influencing factors of aridity index ( AI ) in the growing season of major grain producing areas in Tibet were studied by using climate tendency rate, Mann-Kendal test, Morlet wavelet analysis, GIS hybrid interpolation method, Pearson correlation coefficient, contribution rate analysis and other methods. The results showed that the average AI in the main grain producing areas of Tibet was 1.7, which belonged to the semi-arid area, and the overall trend was decreasing (humidifying) (-0.036/10 a). The linear decreasing trend was different in different regions, and the area around Lhatse County was the most significant (-0.26/10 a). AI had no obvious abrupt change, and had long- and medium-term fluctuation characteristics of 24 years, 6 years. The spatial distribution was uneven, and had the characteristics of ‘shrinking arid area and expanding humid area . The contribution rates of the main climate influencing factors of AI varied in different regions. In general, the contribution rates after quantification was as follows: precipitation (34.9%)>relative humidity (28.4%)>sunshine (19.9%)>maximum temperature (12.4%).
文摘This study aims to assess the synergies and trade-offs of regulating ecosystem services. Ecosystem services are non-linearly interconnected and changes in one service can positively or negatively affect another. We evaluated ecosystem services based on biophysical indicators using an expert scoring system that determines the corresponding soil functions and is part of the existing databases available in Slovakia. This methodological combination enabled us to provide unique mapping and assessment of ecosystem services within Slovakia. Correlation analysis between individual regulating ecosystem services and climate regions, slope, texture, and altitude confirm the statistically significant influence of climate and slope in all agricultural land, arable land, and grassland ecosystems. Statistically significant synergistic effects were established between the regulation of the water regime and the regulation of soil erosion within each climate region, apart from the very warm climate region. Only in a very warm climate region was potential of regulating ecosystem services mutually beneficial for soil erosion control and soil cleaning potential (immobilization of inorganic pollutants).
文摘Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in<sup>2</sup>/s for humidity, 2.993 in<sup>2</sup>/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .
基金jointly supported by the National Key Research and Development Program of China [grant number 2023YFF0805402]the Natural Science Foundation of Jiangsu Province [grant number BK20220031]。
基金supported by the National Natural Science Foundation of China(Grant Nos.42141019 and 42261144687)and STEP(Grant No.2019QZKK0102)supported by the Korea Environmental Industry&Technology Institute(KEITI)through the“Project for developing an observation-based GHG emissions geospatial information map”,funded by the Korea Ministry of Environment(MOE)(Grant No.RS-2023-00232066).
文摘Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of physics in climate science has occasionally been overlooked.Our perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”scenario.Scrutinizing controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical constraints.Furthermore,we provide illustrative examples to guide future assessments and constraints for AI models.Regarding AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online schemes.Additionally,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)principles.Through a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal.
基金supported by the National Natural Science Foundation of China (Grant Nos. 42076202, 42122046, 42206208 and 42261134536)the Open Research Cruise NORC2022-10+NORC2022-303 supported by NSFC shiptime Sharing Projects 42149910+7 种基金the new Cornerstone Science Foundation through the XPLORER PRIZE, DAMO Academy Young Fellow, Youth Innovation Promotion Association, Chinese Academy of SciencesNational Key Scientific and Technological Infrastructure project “Earth System Science Numerical Simulator Facility” (EarthLab)sponsored by the US National Science Foundationsupported by NASA Awards 80NSSC17K0565, 80NSSC21K1191, and 80NSSC22K0046by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy’s Office of Biological & Environmental Research (BER) via National Science Foundation IA 1947282supported by NOAA (Grant No. NA19NES4320002 to CISESS-MD at the University of Maryland)supported by the Young Talent Support Project of Guangzhou Association for Science and Technologyfunded by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) in agreement between INGV, ENEA, and GNV SpA shipping company that provides hospitality on its commercial vessels
文摘The global physical and biogeochemical environment has been substantially altered in response to increased atmospheric greenhouse gases from human activities.In 2023,the sea surface temperature(SST)and upper 2000 m ocean heat content(OHC)reached record highs.The 0–2000 m OHC in 2023 exceeded that of 2022 by 15±10 ZJ(1 Zetta Joules=1021 Joules)(updated IAP/CAS data);9±5 ZJ(NCEI/NOAA data).The Tropical Atlantic Ocean,the Mediterranean Sea,and southern oceans recorded their highest OHC observed since the 1950s.Associated with the onset of a strong El Niño,the global SST reached its record high in 2023 with an annual mean of~0.23℃ higher than 2022 and an astounding>0.3℃ above 2022 values for the second half of 2023.The density stratification and spatial temperature inhomogeneity indexes reached their highest values in 2023.
文摘In the Sahel region, the population depends largely on rain-fed agriculture. In West Africa in particular, climate models turn out to be unable to capture some basic features of present-day climate variability. This study proposes a contribution to the analysis of the evolution of agro-climatic risks in the context of climate variability. Some statistical tests are used on the main variables of the rainy season to determine the trends and the variabilities described by the data series. Thus, the paper provides a statistical modeling of the different agro-climatic risks while the seasonal variability of agro-climatic parameters was analyzed as well as their inter annual variability. The study identifies the probability distributions of agroclimatic risks and the characterization of the rainy season was clarified.
文摘Dear colleagues,We would like to invite you to participate in the special issue of the journal Advances in Polar Science(ISSN 1674-9928)entitled“Past and Present Climatic Change in Antarctica:Geological Proxies and Biological Processes”,which is expected to be published in March 2024 as general issue(Vol.35,No.1).We are honored to invite Dra.Carolina Acosta Hospitaleche,Dr.Javier N.Gelfo,Dr.Marcelo Reguero,Dra.Adolfina Savoretti and Dra.
基金supported by the Second Tibetan Plateau Scientific Expedition and Research(STEP)program[grant number 2019QZKK0102]the Chinese Academy of Sciences[grant number 060GJHZ2023079GC].
文摘Precipitation projections over the Tibetan Plateau(TP)show diversity among existing studies,partly due to model uncertainty.How to develop a reliable projection remains inconclusive.Here,based on the IPCC AR6–assessed likely range of equilibrium climate sensitivity(ECS)and the climatological precipitation performance,the authors constrain the CMIP6(phase 6 of the Coupled Model Intercomparison Project)model projection of summer precipitation and water availability over the TP.The best estimates of precipitation changes are 0.24,0.25,and 0.45 mm d^(−1)(5.9%,6.1%,and 11.2%)under the Shared Socioeconomic Pathway(SSP)scenarios of SSP1–2.6,SSP2–4.5,and SSP5–8.5 from 2050–2099 relative to 1965–2014,respectively.The corresponding constrained projections of water availability measured by precipitation minus evaporation(P–E)are 0.10,0.09,and 0.22 mm d^(−1)(5.7%,4.9%,and 13.2%),respectively.The increase of precipitation and P–E projected by the high-ECS models,whose ECS values are higher than the upper limit of the likely range,are about 1.7 times larger than those estimated by constrained projections.Spatially,there is a larger increase in precipitation and P–E over the eastern TP,while the western part shows a relatively weak difference in precipitation and a drier trend in P–E.The wetter TP projected by the high-ECS models resulted from both an approximately 1.2–1.4 times stronger hydrological sensitivity and additional warming of 0.6℃–1.2℃ under all three scenarios during 2050–2099.This study emphasizes that selecting climate models with climate sensitivity within the likely range is crucial to reducing the uncertainty in the projection of TP precipitation and water availability changes.
基金This research was funded by National Key Research and Development Program of China(No.2018YFA0605601)National Natural Science Foundation of China(No.42077417,41671042).
文摘A set of standard chronologies for tree-ring width(TRW),earlywood width(EWW)and latewood width(LWW)in Pinus tabuliformis Carr.along an altitudi-nal gradient(1450,1400,and 1350 m a.s.l.)on Baiyunshan Mountain,Central China to analyze the effect of varying temperature and precipitation on growth along the gradi-ent.Correlation analyses showed that at all three altitudes and the TRW and EWW chronologies generally had signifi-cant negative correlations with mean and maximum tem-peratures in the current April and May and with minimum temperatures in the prior July and August,but significant positive correlations with precipitation in the current May.Correlations were generally significantly negative between LWW chronologies and all temperatures in the prior July and August,indicating that the prior summer temperature had a strong lag effect on the growth of P.tabuliformis that increased with altitude.The correlation with the standard-ized precipitation evapotranspiration index(SPEI)confirmed that wet conditions in the current May promoted growth of TR and EW at all altitudes.Significant altitudinal differences were also found;at 1400 m,there were significant positive correlations between EWW chronologies and SPEI in the current April and significant negative correlations between LWW chronologies and SPEI in the current September,but these correlations were not significant at 1450 m.At 1350 m,there were also significant negative correlations between the TRW and the EWW chronologies and SPEI in the prior October and the current July and between LWW chronology and SPEI in the current August,but these cor-relations were not significant at 1400 m.Moving correlation results showed a stable response of EWW in relation to the SPEI in the current May at all three altitudes and of LWW to maximum temperature in the prior July-August at 1400 m from 2002 to 2018.The EWW chronology at 1400 m and the LWW chronology at 1450 m were identified as more suitable for climate reconstruction.These results provide a strong scientific basis for forest management decisions and climate reconstructions in Central China.
文摘Like other countries in East Africa, Tanzania has been affected by extreme precipitation incidences both socially and economically. Determining the trend and variability features of extreme precipitation in the country is crucial. This study used data from 28 meteorological stations for 1981-2020 period to give an annual and seasonal analysis of the patterns of 10 ETCCDI’s extreme precipitation indices over the regions. At annual scale, the results showed that increasing trends had high frequency percentage than the decreasing ones, collecting about 76% in total. The decreasing trend was approximately 24%, and most of the stations with increasing percentage in trend are concentrated in Northern coast, Central, West, North-eastern highlands and Lake Victoria Basin. Most of the stations depicted negative trend are concentrated over Southern region. This highlights that extreme precipitation events have increased over the country for the period 1981-2020. At seasonal scale, during October to December (OND);the patterns of extreme precipitation climatic indices except R99p, showed positive significant increasing trend over Lake Victoria Basin and some Western parts of the country. In general, spatial patterns indicate decrease of precipitation over most parts of the country during OND. The seasonal average time series depicted non-significant positive trend during March to April (MAM) season, except for Consecutive Wet Days (CWD) which showed non-significant decreasing trend. Over the highest mountain in Africa, Kilimanjaro;the study has revealed significant decrease in Annual total-wet Precipitation (PRCPTOT), the number of heavy (very heavy) days of precipitation R10 mm (R20 mm) and Consecutive Wet Days (CWD) during MAM season. While the maximum one-day precipitation amount (RX1 day) was observed to decrease significantly over the Mountain during OND season. The result is very important in risk assessment and preparedness perspective in planning climate change mitigation and adaptations for different sectors like Tourism, Agriculture, Water and Energy.
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 National Key Research and Development Program(Grant nos.2022YFC2807203,2022YFB2302701).
文摘The rapid warming of the Arctic,accompanied by glacier and sea ice melt,has significant consequences for the Earth’s climate,ecosystems,and economy.Black carbon(BC)deposition on snow and ice can trigger a significant reduction in snow albedo and accelerate melting of snow and ice in the Arctic.By reviewing the published literatures over the past decades,this work provides an overview of the progress in both the measurement and modeling of BC deposition and its impact on Arctic climate change.In summary,the maximum value of BC deposition appears in the western Russian Arctic(26 ng·g^(–1)),and the minimum value appears in Greenland(3 ng·g^(–1)).BC records in the Arctic ice core already peaked in 1920s and 1970s,and shows a regional difference between Greenland and Canadian Arctic.The different temporal variations of Arctic BC ice core records in different regions are closely related to the large variability of BC emissions and transportation processes across the Arctic region.Model simulations usually underestimate the concentration of BC in snow and ice by 2–3 times,and cannot accurately reflect the seasonal and regional changes in BC deposition.Wet deposition is the main removal mechanism of BC in the Arctic,and observations show different seasonal variations in BC wet deposition in Ny-Ålesund and Barrow.This discrepancy may result from varying contributions of anthropogenic and biomass burning(BB)emissions,given the strong influence by BC from BB emissions at Barrow.Arctic BC deposition significantly influences regional climate change in the Arctic,increasing fire activities in the Arctic have made BB source of Arctic BC more crucial.On average,BC in Arctic snow and ice causes an increase of+0.17 W·m^(–2)in radiative forcing and 8 Gt·a^(–1)in runoff in Greenland.As stressed in the latest Arctic Monitoring and Assessment Programme report,reliable source information and long-term and high-resolution observations on Arctic BC deposition will be crucial for a more comprehensive understanding and a better mitigation strategy of Arctic BC.In the future,it is necessary to collect more observations on BC deposition and the corresponding physical processes(e.g.,snow/ice melting,surface energy balance)in the Arctic to provide reliable data for understanding and clarifying the mechanism of the climatic impacts of BC deposition on Arctic snow and ice.
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(32260415)Guizhou Provincial Science and Technology Project(Qianke Combination Foundation-ZK[2023]Key 010)。
文摘Tsutsusi is one of the eight subgenera of the Rhododendron genus.Four Tsutsusi species,R.indicum,R.simisii,R.oldhamii,and R.schlippenbachii,have high ornamental and medicinal values,resulting in an increasing market demand.These species thrive in cool and humid environments and are widely distributed in Europe and Asia.Whether global climate warming will affect the distribution of these valuable resources remains unclear.Thus,this study analyzed the climatic suitability of these species for the first time on the basis of 1552 geographical distribution points and 19 bioclimatic factors using the maximum entropy model.The results show that a suitable distribution area for all four species would decrease under climate warming.The main bioclimatic factors affecting their distribution are the mean temperature of the coldest quarter for R.indicum,the mean diurnal range for R.simisii,and precipitation of the warmest quarter for R.oldhamii and R.schlippenbachii.In addition,the contribution of the temperature-related bioclimatic factors to the distribution of R.indicum and R.simisii is higher than that of the associated precipitation-related climatic factors;in contrast,the contribution of precipitation-related bioclimatic factors to the distribution of R.oldhamii and R.schlippenbachii is higher than that of the temperature-related climatic factors.These results provide references for the introduction,conservation,sustainable development,and utilization of these four species in the future,and may also provide information with regards to other Rhododendron species.