Land use and cover change(LUCC)is the most direct manifestation of the interaction between anthropological activities and the natural environment on Earth's surface,with significant impacts on the environment and ...Land use and cover change(LUCC)is the most direct manifestation of the interaction between anthropological activities and the natural environment on Earth's surface,with significant impacts on the environment and social economy.Rapid economic development and climate change have resulted in significant changes in land use and cover.The Shiyang River Basin,located in the eastern part of the Hexi Corridor in China,has undergone significant climate change and LUCC over the past few decades.In this study,we used the random forest classification to obtain the land use and cover datasets of the Shiyang River Basin in 1991,1995,2000,2005,2010,2015,and 2020 based on Landsat images.We validated the land use and cover data in 2015 from the random forest classification results(this study),the high-resolution dataset of annual global land cover from 2000 to 2015(AGLC-2000-2015),the global 30 m land cover classification with a fine classification system(GLC_FCS30),and the first Landsat-derived annual China Land Cover Dataset(CLCD)against ground-truth classification results to evaluate the accuracy of the classification results in this study.Furthermore,we explored and compared the spatiotemporal patterns of LUCC in the upper,middle,and lower reaches of the Shiyang River Basin over the past 30 years,and employed the random forest importance ranking method to analyze the influencing factors of LUCC based on natural(evapotranspiration,precipitation,temperature,and surface soil moisture)and anthropogenic(nighttime light,gross domestic product(GDP),and population)factors.The results indicated that the random forest classification results for land use and cover in the Shiyang River Basin in 2015 outperformed the AGLC-2000-2015,GLC_FCS30,and CLCD datasets in both overall and partial validations.Moreover,the classification results in this study exhibited a high level of agreement with the ground truth features.From 1991 to 2020,the area of bare land exhibited a decreasing trend,with changes primarily occurring in the middle and lower reaches of the basin.The area of grassland initially decreased and then increased,with changes occurring mainly in the upper and middle reaches of the basin.In contrast,the area of cropland initially increased and then decreased,with changes occurring in the middle and lower reaches.The LUCC was influenced by both natural and anthropogenic factors.Climatic factors and population contributed significantly to LUCC,and the importance values of evapotranspiration,precipitation,temperature,and population were 22.12%,32.41%,21.89%,and 19.65%,respectively.Moreover,policy interventions also played an important role.Land use and cover in the Shiyang River Basin exhibited fluctuating changes over the past 30 years,with the ecological environment improving in the last 10 years.This suggests that governance efforts in the study area have had some effects,and the government can continue to move in this direction in the future.The findings can provide crucial insights for related research and regional sustainable development in the Shiyang River Basin and other similar arid and semi-arid areas.展开更多
Assessing runoff changes is of great importance especially its responses to the projected future climate change on local scale basins because such analyses are generally done on global and regional scales which may le...Assessing runoff changes is of great importance especially its responses to the projected future climate change on local scale basins because such analyses are generally done on global and regional scales which may lead to generalized conclusions rather than specific ones.Climate change affected the runoff variation in the past in the upper Daqinghe Basin,however,the climate was mainly considered uncertain and still needs further studies,especially its future impacts on runoff for better water resources management and planning.Integrated with a set of climate simulations,a daily conceptual hydrological model(MIKE11-NAM)was applied to assess the impact of climate change on runoff conditions in the Daomaguan,Fuping and Zijingguan basins in the upper Daqinghe Basin.Historical hydrological data(2008–2017)were used to evaluate the applicability of the MIKE11-NAM model.After bias correction,future projected climate change and its impacts on runoff(2025–2054)were analysed and compared to the baseline period(1985–2014)under three shared social economic pathways(SSP1-2.6,SSP2-4.5,and SSP5-8.5)scenarios from Coupled Model Intercomparison Project Phase 6(CMIP6)simulations.The MIKE-11 NAM model was applicable in all three Basins,with both R^(2)and Nash-Sutcliffe Efficiency coefficients greater than 0.6 at daily scale for both calibration(2009–2011)and validation(2012–2017)periods,respectively.Although uncertainties remain,temperature and precipitation are projected to increase compared to the baseline where higher increases in precipitation and temperature are projected to occur under SSP2-4.5 and SSP5-8.5 scenarios,respectively in all the basins.Precipitation changes will range between 12%–19%whereas temperature change will be 2.0℃–2.5℃ under the SSP2-4.5 and SSP5-8.5 scenarios,respectively.In addition,higher warming is projected to occur in colder months than in warmer months.Overall,the runoff of these three basins is projected to respond to projected climate changes differently because runoff is projected to only increase in the Fuping basin under SSP2-4.5 whereas decreases in both Daomaguan and Zijingguan Basins under all scenarios.This study’s findings could be important when setting mitigation strategies for climate change and water resources management.展开更多
该研究通过水提法提取牛骨髓蛋白(Bovine Bone Marrow Protein,BBMP),采用碱性蛋白酶制备牛骨髓蛋白酶解物(Bovine Bone Marrow Alkaline Protease Hydrolysate,BBMP-AH),测定两者的氨基酸含量,同时比较分析结构特征、理化性质以及抗氧...该研究通过水提法提取牛骨髓蛋白(Bovine Bone Marrow Protein,BBMP),采用碱性蛋白酶制备牛骨髓蛋白酶解物(Bovine Bone Marrow Alkaline Protease Hydrolysate,BBMP-AH),测定两者的氨基酸含量,同时比较分析结构特征、理化性质以及抗氧化活性。结果表明,BBMP-AH蛋白含量高于BBMP,BBMP-AH必需氨基酸和疏水性氨基酸含量明显的增加;紫外和红外光谱图谱表明,BBMP及BBMP-AH均显出典型的蛋白吸收峰且酶解后蛋白质二级结构发生了明显的变化;理化性质试验结果表明,BBMP及BBMP-AH的等电点在pH值6左右,远离等电点时,具有较好的理化特性,酸碱性条件下理化性质显著改善。与原蛋白相比,酶解物最高溶解性提高到94.40%、乳化性为1.24 m^(2)/g、乳液稳定性为116.33%,持水性为3.94 g/g,持油性略有降低;BBMP-AH的抗氧化活性显著强于BBMP,均具有较强的DPPH•、•OH、O_(2)^(-)•、ABTS^(+)•清除能力和总还原能力。综上,酶解处理能够改善牛骨髓蛋白理化性质,提高其抗氧化能力,延伸开发应用范围。展开更多
基金supported by the Central Government to Guide Local Technological Development(23ZYQH0298)the Science and Technology Project of Gansu Province(20JR10RA656,22JR5RA416)the Science and Technology Project of Wuwei City(WW2202YFS006).
文摘Land use and cover change(LUCC)is the most direct manifestation of the interaction between anthropological activities and the natural environment on Earth's surface,with significant impacts on the environment and social economy.Rapid economic development and climate change have resulted in significant changes in land use and cover.The Shiyang River Basin,located in the eastern part of the Hexi Corridor in China,has undergone significant climate change and LUCC over the past few decades.In this study,we used the random forest classification to obtain the land use and cover datasets of the Shiyang River Basin in 1991,1995,2000,2005,2010,2015,and 2020 based on Landsat images.We validated the land use and cover data in 2015 from the random forest classification results(this study),the high-resolution dataset of annual global land cover from 2000 to 2015(AGLC-2000-2015),the global 30 m land cover classification with a fine classification system(GLC_FCS30),and the first Landsat-derived annual China Land Cover Dataset(CLCD)against ground-truth classification results to evaluate the accuracy of the classification results in this study.Furthermore,we explored and compared the spatiotemporal patterns of LUCC in the upper,middle,and lower reaches of the Shiyang River Basin over the past 30 years,and employed the random forest importance ranking method to analyze the influencing factors of LUCC based on natural(evapotranspiration,precipitation,temperature,and surface soil moisture)and anthropogenic(nighttime light,gross domestic product(GDP),and population)factors.The results indicated that the random forest classification results for land use and cover in the Shiyang River Basin in 2015 outperformed the AGLC-2000-2015,GLC_FCS30,and CLCD datasets in both overall and partial validations.Moreover,the classification results in this study exhibited a high level of agreement with the ground truth features.From 1991 to 2020,the area of bare land exhibited a decreasing trend,with changes primarily occurring in the middle and lower reaches of the basin.The area of grassland initially decreased and then increased,with changes occurring mainly in the upper and middle reaches of the basin.In contrast,the area of cropland initially increased and then decreased,with changes occurring in the middle and lower reaches.The LUCC was influenced by both natural and anthropogenic factors.Climatic factors and population contributed significantly to LUCC,and the importance values of evapotranspiration,precipitation,temperature,and population were 22.12%,32.41%,21.89%,and 19.65%,respectively.Moreover,policy interventions also played an important role.Land use and cover in the Shiyang River Basin exhibited fluctuating changes over the past 30 years,with the ecological environment improving in the last 10 years.This suggests that governance efforts in the study area have had some effects,and the government can continue to move in this direction in the future.The findings can provide crucial insights for related research and regional sustainable development in the Shiyang River Basin and other similar arid and semi-arid areas.
基金Under the auspices of National Key Research and Development Program of China(No.2021YFD1700500)Natural Science Foundation of Hebei Province,China(No.D2021503001,D2021503011)。
文摘Assessing runoff changes is of great importance especially its responses to the projected future climate change on local scale basins because such analyses are generally done on global and regional scales which may lead to generalized conclusions rather than specific ones.Climate change affected the runoff variation in the past in the upper Daqinghe Basin,however,the climate was mainly considered uncertain and still needs further studies,especially its future impacts on runoff for better water resources management and planning.Integrated with a set of climate simulations,a daily conceptual hydrological model(MIKE11-NAM)was applied to assess the impact of climate change on runoff conditions in the Daomaguan,Fuping and Zijingguan basins in the upper Daqinghe Basin.Historical hydrological data(2008–2017)were used to evaluate the applicability of the MIKE11-NAM model.After bias correction,future projected climate change and its impacts on runoff(2025–2054)were analysed and compared to the baseline period(1985–2014)under three shared social economic pathways(SSP1-2.6,SSP2-4.5,and SSP5-8.5)scenarios from Coupled Model Intercomparison Project Phase 6(CMIP6)simulations.The MIKE-11 NAM model was applicable in all three Basins,with both R^(2)and Nash-Sutcliffe Efficiency coefficients greater than 0.6 at daily scale for both calibration(2009–2011)and validation(2012–2017)periods,respectively.Although uncertainties remain,temperature and precipitation are projected to increase compared to the baseline where higher increases in precipitation and temperature are projected to occur under SSP2-4.5 and SSP5-8.5 scenarios,respectively in all the basins.Precipitation changes will range between 12%–19%whereas temperature change will be 2.0℃–2.5℃ under the SSP2-4.5 and SSP5-8.5 scenarios,respectively.In addition,higher warming is projected to occur in colder months than in warmer months.Overall,the runoff of these three basins is projected to respond to projected climate changes differently because runoff is projected to only increase in the Fuping basin under SSP2-4.5 whereas decreases in both Daomaguan and Zijingguan Basins under all scenarios.This study’s findings could be important when setting mitigation strategies for climate change and water resources management.
