Identifying ecologically vulnerable areas is critical for constructing ecological barriers and precisely controlling ecological risks.With the rapid development of big data and Artificial Intelligence(AI)technologies,...Identifying ecologically vulnerable areas is critical for constructing ecological barriers and precisely controlling ecological risks.With the rapid development of big data and Artificial Intelligence(AI)technologies,many intelligent methods have been developed to support the identification of vulnerable ecological areas.This paper reviews the methodological advancements in identifying ecologically vulnerable areas,including geographic zoning,expert integration,mathematical statistics,geographic information visualization,artificial neural networks,and unsupervised deep learning clustering methods.Additionally,we assessed several classic software tools used in ecology and natural resource management.Based on the review,several urgent research challenges for ecological function zoning research are proposed,such as the application of ecological vulnerability assessment intelligent algorithms,big data collaborative analysis,and the development of automated identification software.Considering the requirements in the Mongolian Plateau,this study proposes future development prospects of methods for identifying ecologically vulnerable area zoning,combined with the new AI research paradigm.They include enhancing the comprehensive analysis of multimodal data,increasing ecological barrier big data collaborative processing,advancing the interpretability of ecological function partitioning algorithms,developing automatic zoning software tools,and pushing the collaborative analysis of geographic big data and citizen science data.展开更多
Evapotranspiration(ET)is of great significance for the ecological environment and water resource utilization in arid and semi-arid regions.The Mongolian Plateau,owing to drought,low rainfall,and extremely uneven distr...Evapotranspiration(ET)is of great significance for the ecological environment and water resource utilization in arid and semi-arid regions.The Mongolian Plateau,owing to drought,low rainfall,and extremely uneven distribution of water resources,has a typical temperate continental climate.A refined understanding of the spatiotemporal distribution of ET in this region will help in establishing regulatory strategies for climate change responses,regional livestock regulation,and grassland degradation suppression.In this study,meteorological station data,precipitation data,and the Penman-Monteith model were used to study the temporal and spatial distribution characteristics of actual ET over the Mongolian Plateau from 2011 to 2022.Results found that:(1)The spatial distribution of ET in the Mongolian Plateau showed a high trend in the north and east and a low trend in the middle and south.There was a significant difference in the regional annual ET,with the highest ET reaching over 500 mm and the lowest being only approximately 70 mm.(2)The annual ET values in 2013,2018,and 2019 were relatively large,varying between 80 and 500 mm,and the overall ET of the Mongolian Plateau first decreased,then increased,and then decreased.(3)The temporal distribution exhibits a unimodal trend of increasing and then decreasing,with July being the turning point.May-September was a period of high ET,with the highest ET exceeding 100 mm.When vegetation coverage was high,precipitation was abundant,and the vegetation ET effect was strong.Winter was a period of low ET,with a maximum ET of approximately 10 mm in January and December;the ET for the month with the lowest value was approximately zero.The quantitative inversion method proposed in this study can provide method and data support for north and central Asia,and other large arid and semi-arid areas.展开更多
After the COP28 Conference,many countries are increasingly concerned about their future practices regarding food security.In North Asia,the Northeast China is the major food production base for the country.Across the ...After the COP28 Conference,many countries are increasingly concerned about their future practices regarding food security.In North Asia,the Northeast China is the major food production base for the country.Across the border,the economy of Mongolia is heavily reliant on agricultural production and animal husbandry.In recent years,climatic extremes such as droughts and floods,combined with human-induced overgrazing,have posed alarming threats to food security.This review illustrates the challenges and constraints these two countries are facing due to climate changes and summarizes the existing measures and established programs in both countries.Furthermore,we develop the“climate resilient agriculture”(CRA)framework for improving agricultural resilience.This framework emphasizes the importance of international institutions,such as the World Bank,and developed countries to provide more financial and technological support to bolster climate resilience in Northern Asia.Finally,we conclude by encouraging cross-border co-production and collaborations among governments to implement the CRA framework to tackle future climatic challenges.展开更多
Natural and anthropogenic disturbances accelerate land degradation(LD)in arid,semi-arid,and dry sub-humid areas,leading to reduced land quality and productivity,loss of biodiversity,degradation of ecosystem services,a...Natural and anthropogenic disturbances accelerate land degradation(LD)in arid,semi-arid,and dry sub-humid areas,leading to reduced land quality and productivity,loss of biodiversity,degradation of ecosystem services,and a decline in the quality of life of local people.To address this issue,the United Nations Convention to Combat Desertification(UNCCD)has set a target for LD neutrality(LDN).However,quantifying and comparing the status of LD at global or regional scales remains challenging due to the lack of coherent quantitative methods and tools.In this study,we focused on Mongolia,a region with significant LD problems,to examine patterns of LD and changes from 2015 to 2020,accounting for regional differences.Trends.Earth was used,as recommended by the UNCCD.The main findings are as follows:(1)Overall,the degraded land area in Mongolia accounted for 12.11%of the total land area,predominantly located in the southwest desert and desert steppe,gradually spreading to the northeast steppe.(2)The areas showing improvement in the land productivity index and degradation were 17.62%and 11.79%,respectively,with the most severely degraded areas concentrated in the southern desert and desert steppe regions.(3)The areas of improvement and degradation in the land cover index were 1.80%and 0.16%,respectively,with degraded areas scattered across regions of steppe,high mountains,and mountain taiga.(4)The areas of improvement and degradation in the land organic carbon index were 1.54%and 0.22%,respectively,with degradation primarily observed in adjacent areas of mountain taiga,steppe,and desert steppe.(5)The improved area(2.999×10^(5)km^(2))of LDN are more than the degraded area(1.895×10^(5)km^(2)),indicating a positive trend toward LDN in Mongolia.展开更多
The permafrost region is one of the most sensitive areas to climate change.With global warming,the Mongolian Plateau permafrost is rapidly degrading,and its vegetation ecosystem is seriously threatened.To address this...The permafrost region is one of the most sensitive areas to climate change.With global warming,the Mongolian Plateau permafrost is rapidly degrading,and its vegetation ecosystem is seriously threatened.To address this challenge,it is essential to understand the impact of climate change on vegetation at different permafrost degradation stages on the Mongolian Plateau.Based on the general permafrost distribution,in this study,we divided different permafrost regions and explored the response of vegetation to climate change at different stages of permafrost degradation by the idea of“space instead of time”from 2014 to 2023.The results of the study showed that:(1)Normalized difference vegetation index(NDVI)values showed a decreasing trend,and the proportion of the decreasing region was in the order of sporadic permafrost region>isolated and sparse permafrost region>continuous and discontinuous permafrost regions.(2)The main controlling factors of vegetation growth in permafrost regions are different,air temperature is the main controlling factor of vegetation growth in isolated and sparse permafrost region(r=-0.736)and sporadic permafrost regions(r=-0.522),and precipitation is the main controlling factor of vegetation growth in continuous and discontinuous permafrost region(r=-0.498).(3)The response of NDVI to climate change varies at different stages of permafrost degradation.In the early stages of permafrost degradation,increased land surface temperature(LST)and air temperature favored vegetation growth and increased vegetation cover,whereas increased precipitation impeded vegetation growth;as the permafrost degraded,increased LST and air temperature impeded vegetation growth,whereas increased precipitation promoted vegetation growth.展开更多
The Mongolian Plateau,a vital ecological barrier in northern China,is of great importance for studying vegetation dynamics in Mongolia against the background of climate warming.Such studies can enhance our understandi...The Mongolian Plateau,a vital ecological barrier in northern China,is of great importance for studying vegetation dynamics in Mongolia against the background of climate warming.Such studies can enhance our understanding of regional vegetation responses to global warming and contribute to the establishment of a stronger ecological barrier in northern China.Here,we analyzed the spatial and temporal characteristics of the NDVI(normalized difference vegetation index)in Mongolia using 8 km resolution GIMMS NDVI3g data from 1990 to 2022,along with temperature,precipitation,and elevation data.Trend analysis and correlation methods were used to examine the relationships between the NDVI and temperature,as well as precipitation.The results showed four important aspects of these relationships.(1)The NDVI in Mongolia increased significantly from 1990 to 2022 at a rate of 0.0015 yr^(-1)(P<0.05).(2)Mongolia’s NDVI increased from 1990 to 2022 in 60.73%of the country.Of this total,the area with a significant increase accounted for 31.67%and was concentrated on the eastern and western edges.The area experiencing a significant decrease accounted for 15.67%and was mainly located on the southwestern edges.(3)The NDVI analysis revealed significant increasing trends in all regions except for those at elevations of 1500-2000 m.The greatest rate of increase was observed between 500 and 1000 m,and the increasing trend weakened as elevation continued to increase before gradually becoming significant again.Additionally,the NDVI increased significantly across different slopes,and the rate of increase decreased as the slope increased.(4)From 1990 to 2022,Mongolia’s NDVI was mostly negatively correlated with temperature.This occurred over 66.75%of the total land area,with 17.21%of the region exhibiting a significant negative correlation,mainly in the southwest.Conversely,the NDVI demonstrated a positive correlation with precipitation,encompassing 86.71%of the total land area.Approximately 40.44%of the region had a significant positive correlation,primarily in the southwest.In conclusion,throughout the experimental period,the vegetation state in Mongolia improved.However,due to the warming and drying climate,more attention should be paid to vegetation degradation in the south-central region.展开更多
The Mongolian Plateau(MP),situated in the transitional zone between the Siberian taiga and the arid grasslands of Central Asia,plays a significant role as an Ecological Barrier(EB)with crucial implications for ecologi...The Mongolian Plateau(MP),situated in the transitional zone between the Siberian taiga and the arid grasslands of Central Asia,plays a significant role as an Ecological Barrier(EB)with crucial implications for ecological and resource security in Northeast Asia.EB is a vast concept and a complex issue related to many aspects such as water,land,air,vegetation,animals,and people,et al.It is very difficult to understand the whole of EB without a comprehensive perspective,that traditional diverse studies cannot cover.Big data and artificial intelligence(AI)have enabled a shift in the research paradigm.Faced with these requirements,this study identified issues in the construction of EB on MP from a big data perspective.This includes the issues,progress,and future recommendations for EB construction-related studies using big data and AI.Current issues cover the status of theoretical studies,technical bottlenecks,and insufficient synergistic analyses related to EB construction.Research progress introduces advances in scientific research driven by big data in three key areas of MP:natural resources,the ecological environment,and sustainable development.For the future development of EB construction on MP,it is recommended to utilize big data and intelligent computing technologies,integrate extensive regional data resources,develop precise algorithms and automated tools,and construct a big data collaborative innovation platform.This study aims to call for more attention to big data and AI applications in EB studies,thereby supporting the achievement of sustainable development goals in the MP and enhancing the research paradigm transforming in the fields of resources and the environment.展开更多
Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the ag...Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. Based on the Tropical Rainfall Measuring Mission Satellite（TRMM） 3 B43 precipitation data, we used the Precipitation Abnormity Percentage drought model to study the monthly spatio-temporal distribution of drought in south region of N50° of the Belt and Road area. It was observed that drought during winter was mainly distributed in Northeast Asia, Southeast Asia, and South Asia, while it was mainly distributed in Central Asia and West Asia during summer. The occurrence of historical droughts indicates an obvious seasonal cycle. The regional variations in drought were analyzed using the Breaks for Additive Season and Trend tool（BFAST） in six sub-regions according to the spatial distribution of six economic corridors in the Belt and Road area. The average drought conditions over the 18 years show a slight decreasing trend in Northeast Asia, West Asia, North Africa, South Asia, Central and Eastern Europe, and a slight increasing trend in Central Asia. However, it was a fluctuating pattern of first increasing and then decreasing in Southeast Asia. The results indicate that the total drought area in the Belt and Road region showed a general decreasing trend at a rate of 40,260 km^2 per year from 1998 to 2015.展开更多
Grassland degradation in Altay Prefecture is of considerable concern as it is a threat that hinders the sustainable development of the local economy and the stable operation of the livestock industry.Quantitative asse...Grassland degradation in Altay Prefecture is of considerable concern as it is a threat that hinders the sustainable development of the local economy and the stable operation of the livestock industry.Quantitative assessment of the relative contributions of climate change and human activities,which are considered as the dominant triggers of grassland degradation,to grassland variation is crucial for understanding the grassland degradation mechanism and mitigating the degraded grassland in Altay Prefecture.In this paper,the Carnegie-Ames-Stanford Approach model and the Thornthwaite memorial model were adopted to simulate the actual net primary productivity(NPP_(A))and potential net primary productivity(NPP_(P))in the Altay Prefecture from 2000 to 2019.Meanwhile,the difference between potential NPP and actual NPP was employed to reflect the effects of human activities(NPP_(H))on the grassland.On this basis,we validated the viability of the simulated NPP using the Pearson correlation coefficient,investigated the spatiotemporal variability of grassland productivity,and established comprehensive scenarios to quantitatively assess the relative roles of climate change and human activities on grassland in Altay prefecture.The results indicate three main points.(1)The simulated NPP_(A) was highly consistent with the MOD17 A3 dataset in spatial distribution.(2)Regions with an increased NPP_(A) accounted for 70.53% of the total grassland,whereas 29.47% of the total grassland area experienced a decrease.At the temporal scale,the NPP_(A) presented a slightly increasing trend(0.83 g C m^(-2) yr^(-1))over the study period,while the trends of NPP_(P) and NPP_(H) were reduced(-1.31 and-2.15 g C m^(-2) yr^(-1)).(3)Compared with climate change,human activities played a key role in the process of grassland restoration,as 66.98% of restored grassland resulted from it.In contrast,inter-annual climate change is the primary cause of grassland degradation,as it influenced 55.70% of degraded grassland.These results could shed light on the mechanisms of grassland variation caused by climate change and human activities,and they can be applied to further develop efficient measures to combat desertification in Altay Prefecture.展开更多
Mongolia is an important part of the Belt and Road Initiative"China-Mongolia-Russia Economic Corridor"and a region that has been severely affected by global climate change.Changes in grassland production hav...Mongolia is an important part of the Belt and Road Initiative"China-Mongolia-Russia Economic Corridor"and a region that has been severely affected by global climate change.Changes in grassland production have had a profound impact on the sustainable development of the region.Our study explored an optimal model for estimating grassland production in Mongolia and discovered its temporal and spatial distributions.Three estimation models were established using a statistical analysis method based on EVI,MSAVI,NDVI,and PsnNet from Moderate Resolution Imaging Spectroradiometer(MODIS)remote sensing data and measured data.A model evaluation and accuracy comparison showed that an exponential model based on MSAVI was the best simulation(model accuracy 78%).This was selected to estimate the grassland production in central and eastern Mongolia from 2006 to 2015.The results show that the grassland production in the study area had a significantly fluctuating trend for the decade study;a slight overall increasing trend was observed.For the first five years,the grassland production decreased slowly,whereas in the latter five years,significant fluctuations were observed.The grassland production(per unit yield)gradually increased from the southwest to northeast.In most provinces of the study area,the production was above 1000 kg ha with the largest production in Hentiy,at 3944.35 kg ha.The grassland production(total yield)varied greatly among the provinces,with Kent showing the highest production,2341.76x1〇4 t.Results also indicate that the trend in grassland production along the China-Mongolia railway was generally consistent with that of the six provinces studied.展开更多
Incarvillea younghusbandii is a well-known Tibetan medicinal plant with considerable development and research value distributed widely throughout the Tibetan plateau.It is important to study spatial distribution patte...Incarvillea younghusbandii is a well-known Tibetan medicinal plant with considerable development and research value distributed widely throughout the Tibetan plateau.It is important to study spatial distribution patterns of the plant in order to develop effective protection measures.Based on field survey work and environmental data, the potential geographic distribution of Incarvillea younghusbandii was delineated using a Maximum Entropy (Maxent)model with 28environmental variables that screened for climate,topography,human activity and biological factors.Our results showed that the main geographic range of Incarvillea younghusbandii included the valley between the Yarlung Zangbo river and the Duoxiong Zangbo river,the valley in the middle section of the Himalaya Mountains,and the area between the north side of the east section of the Himalayas and the south bank of the middle reach of the Yarlung Zangbo river.Distribution may spread to parts of the eastern Himalayas.The Jackknife test indicated that soil types,ratio of precipitation to air temperature,extreme atmospheric pressure differences and annual precipitation were the most important predictive factors for the model,while other variables made relatively small contributions.展开更多
Altay region is located in the northern part of Xinjiang,and has complex and diverse internal geomorphic types,undulating terrain and a fragile ecosystem.Studying the impact of land use changes on habitat quality is o...Altay region is located in the northern part of Xinjiang,and has complex and diverse internal geomorphic types,undulating terrain and a fragile ecosystem.Studying the impact of land use changes on habitat quality is of great significance to regional ecological protection and development,rational planning and utilization,and ensuring the sustainable development of the ecological environment.Based on the InVEST model,combined with land use panel data and topographic relief data of the Altay region,this paper studied the habitat quality from 1995 to 2018.The results show that cultivated land,water area and construction land increased gradually from 1995 to 2018,while grassland and unused land decreased.Forestland remained stable in the first five periods,but increased significantly in 2018.During 1995-2018,all land use types were transferred,mainly between cultivated land,forestland,grassland and unused land in the flat and slightly undulating areas.Poor habitat quality was dominant during 1995-2018.Habitat quality decreased significantly in 2015,which was related to the rapid expansion of cultivated and construction land as threat sources,as well as the decrease of forest and grassland as sensitive factors.However,habitat quality improved significantly in 2018,because a large amount of cultivated land and unused land were converted into forest land and grassland with high habitat suitability.Land use type has an important influence on habitat quality.The distribution characteristics of habitat quality for topographic relief types from good to bad were:large undulating area>medium undulating area>small undulating area>flat area>slightly undulating area.The findings of this study are of great significance for coordinating social,economic,and ecological development in this region and in similar areas.展开更多
基金The National Key Research and Development Program(2022YFE0119200)The Key Research and Development and Achievement Transformation Plan Project of Inner Mongolia Autonomous Region(2023KJHZ0027)+1 种基金The Key Project of Innovation LREIS(KPI006)The Construction Project of China Knowledge Center for Engineering Sciences and Technology(CKCEST-2023-1-5)。
文摘Identifying ecologically vulnerable areas is critical for constructing ecological barriers and precisely controlling ecological risks.With the rapid development of big data and Artificial Intelligence(AI)technologies,many intelligent methods have been developed to support the identification of vulnerable ecological areas.This paper reviews the methodological advancements in identifying ecologically vulnerable areas,including geographic zoning,expert integration,mathematical statistics,geographic information visualization,artificial neural networks,and unsupervised deep learning clustering methods.Additionally,we assessed several classic software tools used in ecology and natural resource management.Based on the review,several urgent research challenges for ecological function zoning research are proposed,such as the application of ecological vulnerability assessment intelligent algorithms,big data collaborative analysis,and the development of automated identification software.Considering the requirements in the Mongolian Plateau,this study proposes future development prospects of methods for identifying ecologically vulnerable area zoning,combined with the new AI research paradigm.They include enhancing the comprehensive analysis of multimodal data,increasing ecological barrier big data collaborative processing,advancing the interpretability of ecological function partitioning algorithms,developing automatic zoning software tools,and pushing the collaborative analysis of geographic big data and citizen science data.
基金The National Natural Science Foundation of China(32161143025)The Science&Technology Fundamental Resources Investigation Program of China(2022FY101905)+4 种基金The National Key R&D Program of China(2022YFE0119200)The Mongolian Foundation for Science and Technology(NSFC_2022/01,CHN2022/276)The Key R&D and Achievement Transformation Plan Project in Inner Mongolia Autonomous Region(2023KJHZ0027)The Key Project of Innovation LREIS(KPI006)The Construction Project of China Knowledge Center for Engineering Sciences and Technology(CKCEST-2023-1-5)。
文摘Evapotranspiration(ET)is of great significance for the ecological environment and water resource utilization in arid and semi-arid regions.The Mongolian Plateau,owing to drought,low rainfall,and extremely uneven distribution of water resources,has a typical temperate continental climate.A refined understanding of the spatiotemporal distribution of ET in this region will help in establishing regulatory strategies for climate change responses,regional livestock regulation,and grassland degradation suppression.In this study,meteorological station data,precipitation data,and the Penman-Monteith model were used to study the temporal and spatial distribution characteristics of actual ET over the Mongolian Plateau from 2011 to 2022.Results found that:(1)The spatial distribution of ET in the Mongolian Plateau showed a high trend in the north and east and a low trend in the middle and south.There was a significant difference in the regional annual ET,with the highest ET reaching over 500 mm and the lowest being only approximately 70 mm.(2)The annual ET values in 2013,2018,and 2019 were relatively large,varying between 80 and 500 mm,and the overall ET of the Mongolian Plateau first decreased,then increased,and then decreased.(3)The temporal distribution exhibits a unimodal trend of increasing and then decreasing,with July being the turning point.May-September was a period of high ET,with the highest ET exceeding 100 mm.When vegetation coverage was high,precipitation was abundant,and the vegetation ET effect was strong.Winter was a period of low ET,with a maximum ET of approximately 10 mm in January and December;the ET for the month with the lowest value was approximately zero.The quantitative inversion method proposed in this study can provide method and data support for north and central Asia,and other large arid and semi-arid areas.
基金The National Natural Science Foundation of China(32161143025)The Mongolian Foundation for Science and Technology(NSFC_2022/01,CHN2022/276)+7 种基金The National Natural Science Foundation of China(W2432029)The National Key R&D Program of China(2022YFE0119200)The Key Project of Innovation LREIS(KPI006)The National University of Mongolia(P2023-4429,P2022-4256)The Ningbo Natural Science Foundation(2023J193)The Hong Kong Environmental Council Fund(ECF:44/2020)The Natural Science Foundation of Zhejiang ProvinceChina(ZJWY23E090024)。
文摘After the COP28 Conference,many countries are increasingly concerned about their future practices regarding food security.In North Asia,the Northeast China is the major food production base for the country.Across the border,the economy of Mongolia is heavily reliant on agricultural production and animal husbandry.In recent years,climatic extremes such as droughts and floods,combined with human-induced overgrazing,have posed alarming threats to food security.This review illustrates the challenges and constraints these two countries are facing due to climate changes and summarizes the existing measures and established programs in both countries.Furthermore,we develop the“climate resilient agriculture”(CRA)framework for improving agricultural resilience.This framework emphasizes the importance of international institutions,such as the World Bank,and developed countries to provide more financial and technological support to bolster climate resilience in Northern Asia.Finally,we conclude by encouraging cross-border co-production and collaborations among governments to implement the CRA framework to tackle future climatic challenges.
基金The National Natural Science Foundation of China(32161143025)The Science&Technology Fundamental Resources Investigation Program of China(2022FY101905)+4 种基金The National Key R&D Program of China(2022YFE0119200)The Mongolian Foundation for Science and Technology(NSFC_2022/01,CHN2022/276)The Key R&D and Achievement Transformation Plan Project in Inner Mongolia Autonomous Region(2023KJHZ0027)The Key Project of Innovation LREIS(KPI006)The Construction Project of China Knowledge Center for Engineering Sciences and Technology(CKCEST-2023-1-5)。
文摘Natural and anthropogenic disturbances accelerate land degradation(LD)in arid,semi-arid,and dry sub-humid areas,leading to reduced land quality and productivity,loss of biodiversity,degradation of ecosystem services,and a decline in the quality of life of local people.To address this issue,the United Nations Convention to Combat Desertification(UNCCD)has set a target for LD neutrality(LDN).However,quantifying and comparing the status of LD at global or regional scales remains challenging due to the lack of coherent quantitative methods and tools.In this study,we focused on Mongolia,a region with significant LD problems,to examine patterns of LD and changes from 2015 to 2020,accounting for regional differences.Trends.Earth was used,as recommended by the UNCCD.The main findings are as follows:(1)Overall,the degraded land area in Mongolia accounted for 12.11%of the total land area,predominantly located in the southwest desert and desert steppe,gradually spreading to the northeast steppe.(2)The areas showing improvement in the land productivity index and degradation were 17.62%and 11.79%,respectively,with the most severely degraded areas concentrated in the southern desert and desert steppe regions.(3)The areas of improvement and degradation in the land cover index were 1.80%and 0.16%,respectively,with degraded areas scattered across regions of steppe,high mountains,and mountain taiga.(4)The areas of improvement and degradation in the land organic carbon index were 1.54%and 0.22%,respectively,with degradation primarily observed in adjacent areas of mountain taiga,steppe,and desert steppe.(5)The improved area(2.999×10^(5)km^(2))of LDN are more than the degraded area(1.895×10^(5)km^(2)),indicating a positive trend toward LDN in Mongolia.
基金The National Natural Science Foundation of China(32161143025)The Science&Technology Fundamental Resources Investigation Program of China(2022FY101905)+4 种基金The National Key R&D Program of China(2022YFE0119200)The Mongolian Foundation for Science and Technology(NSFC_2022/01,CHN2022/276)The Key R&D and Achievement Transformation Plan Project in Inner Mongolia Autonomous Region(2023KJHZ0027)The Key Project of Innovation LREIS(KPI006)The Construction Project of China Knowledge Center for Engineering Sciences and Technology(CKCEST-2023-1-5)。
文摘The permafrost region is one of the most sensitive areas to climate change.With global warming,the Mongolian Plateau permafrost is rapidly degrading,and its vegetation ecosystem is seriously threatened.To address this challenge,it is essential to understand the impact of climate change on vegetation at different permafrost degradation stages on the Mongolian Plateau.Based on the general permafrost distribution,in this study,we divided different permafrost regions and explored the response of vegetation to climate change at different stages of permafrost degradation by the idea of“space instead of time”from 2014 to 2023.The results of the study showed that:(1)Normalized difference vegetation index(NDVI)values showed a decreasing trend,and the proportion of the decreasing region was in the order of sporadic permafrost region>isolated and sparse permafrost region>continuous and discontinuous permafrost regions.(2)The main controlling factors of vegetation growth in permafrost regions are different,air temperature is the main controlling factor of vegetation growth in isolated and sparse permafrost region(r=-0.736)and sporadic permafrost regions(r=-0.522),and precipitation is the main controlling factor of vegetation growth in continuous and discontinuous permafrost region(r=-0.498).(3)The response of NDVI to climate change varies at different stages of permafrost degradation.In the early stages of permafrost degradation,increased land surface temperature(LST)and air temperature favored vegetation growth and increased vegetation cover,whereas increased precipitation impeded vegetation growth;as the permafrost degraded,increased LST and air temperature impeded vegetation growth,whereas increased precipitation promoted vegetation growth.
基金The National Key R&D Program of China(2022YFE0119200)The National Natural Science Foundation of China(41977059,41501571)。
文摘The Mongolian Plateau,a vital ecological barrier in northern China,is of great importance for studying vegetation dynamics in Mongolia against the background of climate warming.Such studies can enhance our understanding of regional vegetation responses to global warming and contribute to the establishment of a stronger ecological barrier in northern China.Here,we analyzed the spatial and temporal characteristics of the NDVI(normalized difference vegetation index)in Mongolia using 8 km resolution GIMMS NDVI3g data from 1990 to 2022,along with temperature,precipitation,and elevation data.Trend analysis and correlation methods were used to examine the relationships between the NDVI and temperature,as well as precipitation.The results showed four important aspects of these relationships.(1)The NDVI in Mongolia increased significantly from 1990 to 2022 at a rate of 0.0015 yr^(-1)(P<0.05).(2)Mongolia’s NDVI increased from 1990 to 2022 in 60.73%of the country.Of this total,the area with a significant increase accounted for 31.67%and was concentrated on the eastern and western edges.The area experiencing a significant decrease accounted for 15.67%and was mainly located on the southwestern edges.(3)The NDVI analysis revealed significant increasing trends in all regions except for those at elevations of 1500-2000 m.The greatest rate of increase was observed between 500 and 1000 m,and the increasing trend weakened as elevation continued to increase before gradually becoming significant again.Additionally,the NDVI increased significantly across different slopes,and the rate of increase decreased as the slope increased.(4)From 1990 to 2022,Mongolia’s NDVI was mostly negatively correlated with temperature.This occurred over 66.75%of the total land area,with 17.21%of the region exhibiting a significant negative correlation,mainly in the southwest.Conversely,the NDVI demonstrated a positive correlation with precipitation,encompassing 86.71%of the total land area.Approximately 40.44%of the region had a significant positive correlation,primarily in the southwest.In conclusion,throughout the experimental period,the vegetation state in Mongolia improved.However,due to the warming and drying climate,more attention should be paid to vegetation degradation in the south-central region.
基金The National Natural Science Foundation of China(32161143025)The National Key R&D Program of China(2022YFE0119200)+4 种基金The Science&Technology Fundamental Resources Investigation Program of China(2022FY101902)The Mongolian Foundation for Science and Technology(NSFC_2022/01,CHN2022/276)The Key R&D and Achievement Transformation Plan Project in Inner Mongolia Autonomous Region(2023KJHZ0027)The Key Project of Innovation LREIS(KPI006)The Construction Project of China Knowledge Center for Engineering Sciences and Technology(CKCEST-2023-1-5)。
文摘The Mongolian Plateau(MP),situated in the transitional zone between the Siberian taiga and the arid grasslands of Central Asia,plays a significant role as an Ecological Barrier(EB)with crucial implications for ecological and resource security in Northeast Asia.EB is a vast concept and a complex issue related to many aspects such as water,land,air,vegetation,animals,and people,et al.It is very difficult to understand the whole of EB without a comprehensive perspective,that traditional diverse studies cannot cover.Big data and artificial intelligence(AI)have enabled a shift in the research paradigm.Faced with these requirements,this study identified issues in the construction of EB on MP from a big data perspective.This includes the issues,progress,and future recommendations for EB construction-related studies using big data and AI.Current issues cover the status of theoretical studies,technical bottlenecks,and insufficient synergistic analyses related to EB construction.Research progress introduces advances in scientific research driven by big data in three key areas of MP:natural resources,the ecological environment,and sustainable development.For the future development of EB construction on MP,it is recommended to utilize big data and intelligent computing technologies,integrate extensive regional data resources,develop precise algorithms and automated tools,and construct a big data collaborative innovation platform.This study aims to call for more attention to big data and AI applications in EB studies,thereby supporting the achievement of sustainable development goals in the MP and enhancing the research paradigm transforming in the fields of resources and the environment.
基金Construction Project of China Knowledge Center for Engineering Sciences and Technology(CKCEST-2017-3-1)Cultivate Project of Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Science(TSYJS03)National University of Mongolia(P2017-2396)
文摘Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. Based on the Tropical Rainfall Measuring Mission Satellite（TRMM） 3 B43 precipitation data, we used the Precipitation Abnormity Percentage drought model to study the monthly spatio-temporal distribution of drought in south region of N50° of the Belt and Road area. It was observed that drought during winter was mainly distributed in Northeast Asia, Southeast Asia, and South Asia, while it was mainly distributed in Central Asia and West Asia during summer. The occurrence of historical droughts indicates an obvious seasonal cycle. The regional variations in drought were analyzed using the Breaks for Additive Season and Trend tool（BFAST） in six sub-regions according to the spatial distribution of six economic corridors in the Belt and Road area. The average drought conditions over the 18 years show a slight decreasing trend in Northeast Asia, West Asia, North Africa, South Asia, Central and Eastern Europe, and a slight increasing trend in Central Asia. However, it was a fluctuating pattern of first increasing and then decreasing in Southeast Asia. The results indicate that the total drought area in the Belt and Road region showed a general decreasing trend at a rate of 40,260 km^2 per year from 1998 to 2015.
基金The Science and Technology Project of Xizang Autonomous Region(XZ201901-GA-07)The Key Research and Development Project of Sichuan Science and Technology Department(2021YFQ0042)The Science and Technology Bureau of Altay Region in Yili Kazak Autonomous Prefecture(Y99M4600AL)。
文摘Grassland degradation in Altay Prefecture is of considerable concern as it is a threat that hinders the sustainable development of the local economy and the stable operation of the livestock industry.Quantitative assessment of the relative contributions of climate change and human activities,which are considered as the dominant triggers of grassland degradation,to grassland variation is crucial for understanding the grassland degradation mechanism and mitigating the degraded grassland in Altay Prefecture.In this paper,the Carnegie-Ames-Stanford Approach model and the Thornthwaite memorial model were adopted to simulate the actual net primary productivity(NPP_(A))and potential net primary productivity(NPP_(P))in the Altay Prefecture from 2000 to 2019.Meanwhile,the difference between potential NPP and actual NPP was employed to reflect the effects of human activities(NPP_(H))on the grassland.On this basis,we validated the viability of the simulated NPP using the Pearson correlation coefficient,investigated the spatiotemporal variability of grassland productivity,and established comprehensive scenarios to quantitatively assess the relative roles of climate change and human activities on grassland in Altay prefecture.The results indicate three main points.(1)The simulated NPP_(A) was highly consistent with the MOD17 A3 dataset in spatial distribution.(2)Regions with an increased NPP_(A) accounted for 70.53% of the total grassland,whereas 29.47% of the total grassland area experienced a decrease.At the temporal scale,the NPP_(A) presented a slightly increasing trend(0.83 g C m^(-2) yr^(-1))over the study period,while the trends of NPP_(P) and NPP_(H) were reduced(-1.31 and-2.15 g C m^(-2) yr^(-1)).(3)Compared with climate change,human activities played a key role in the process of grassland restoration,as 66.98% of restored grassland resulted from it.In contrast,inter-annual climate change is the primary cause of grassland degradation,as it influenced 55.70% of degraded grassland.These results could shed light on the mechanisms of grassland variation caused by climate change and human activities,and they can be applied to further develop efficient measures to combat desertification in Altay Prefecture.
基金The Strategic Priority Research Program(Class A)of the Chinese Academy of Sciences(XDA2003020302,XDA19040501)The Construction Project of the China Knowledge Center for Engineering Sciences and Technology(CKCEST-2019-3-6)The 13th Five-year Informatization Plan of Chinese Academy of Sciences(XXH13505-07)
文摘Mongolia is an important part of the Belt and Road Initiative"China-Mongolia-Russia Economic Corridor"and a region that has been severely affected by global climate change.Changes in grassland production have had a profound impact on the sustainable development of the region.Our study explored an optimal model for estimating grassland production in Mongolia and discovered its temporal and spatial distributions.Three estimation models were established using a statistical analysis method based on EVI,MSAVI,NDVI,and PsnNet from Moderate Resolution Imaging Spectroradiometer(MODIS)remote sensing data and measured data.A model evaluation and accuracy comparison showed that an exponential model based on MSAVI was the best simulation(model accuracy 78%).This was selected to estimate the grassland production in central and eastern Mongolia from 2006 to 2015.The results show that the grassland production in the study area had a significantly fluctuating trend for the decade study;a slight overall increasing trend was observed.For the first five years,the grassland production decreased slowly,whereas in the latter five years,significant fluctuations were observed.The grassland production(per unit yield)gradually increased from the southwest to northeast.In most provinces of the study area,the production was above 1000 kg ha with the largest production in Hentiy,at 3944.35 kg ha.The grassland production(total yield)varied greatly among the provinces,with Kent showing the highest production,2341.76x1〇4 t.Results also indicate that the trend in grassland production along the China-Mongolia railway was generally consistent with that of the six provinces studied.
基金National Key Technologies Research and Development Program of China(2014BAL07B02)Tibet Autonomous Region Science-technology Support Projects(201DKJGX01-38)
文摘Incarvillea younghusbandii is a well-known Tibetan medicinal plant with considerable development and research value distributed widely throughout the Tibetan plateau.It is important to study spatial distribution patterns of the plant in order to develop effective protection measures.Based on field survey work and environmental data, the potential geographic distribution of Incarvillea younghusbandii was delineated using a Maximum Entropy (Maxent)model with 28environmental variables that screened for climate,topography,human activity and biological factors.Our results showed that the main geographic range of Incarvillea younghusbandii included the valley between the Yarlung Zangbo river and the Duoxiong Zangbo river,the valley in the middle section of the Himalaya Mountains,and the area between the north side of the east section of the Himalayas and the south bank of the middle reach of the Yarlung Zangbo river.Distribution may spread to parts of the eastern Himalayas.The Jackknife test indicated that soil types,ratio of precipitation to air temperature,extreme atmospheric pressure differences and annual precipitation were the most important predictive factors for the model,while other variables made relatively small contributions.
基金The Science and Technology Bureau of Altay Region in Yili Kazak Autonomous Prefecture(Y99M4600AL)。
文摘Altay region is located in the northern part of Xinjiang,and has complex and diverse internal geomorphic types,undulating terrain and a fragile ecosystem.Studying the impact of land use changes on habitat quality is of great significance to regional ecological protection and development,rational planning and utilization,and ensuring the sustainable development of the ecological environment.Based on the InVEST model,combined with land use panel data and topographic relief data of the Altay region,this paper studied the habitat quality from 1995 to 2018.The results show that cultivated land,water area and construction land increased gradually from 1995 to 2018,while grassland and unused land decreased.Forestland remained stable in the first five periods,but increased significantly in 2018.During 1995-2018,all land use types were transferred,mainly between cultivated land,forestland,grassland and unused land in the flat and slightly undulating areas.Poor habitat quality was dominant during 1995-2018.Habitat quality decreased significantly in 2015,which was related to the rapid expansion of cultivated and construction land as threat sources,as well as the decrease of forest and grassland as sensitive factors.However,habitat quality improved significantly in 2018,because a large amount of cultivated land and unused land were converted into forest land and grassland with high habitat suitability.Land use type has an important influence on habitat quality.The distribution characteristics of habitat quality for topographic relief types from good to bad were:large undulating area>medium undulating area>small undulating area>flat area>slightly undulating area.The findings of this study are of great significance for coordinating social,economic,and ecological development in this region and in similar areas.
