There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficien...There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficient.We simulated the spatiotemporal dynamics of ESs(e.g.,carbon storage,water yield,habitat quality,and soil conservation)and ERs in the upper reach of the Yellow River(URYR)from 2000 to 2100.Additionally,we explored their relationships by combining the InVEST model and a landscape ecological risk model with CMIP6 data.Our main findings showed that regional ERs change in response to land use and environmental dynamics.Specifically,the ER area decreased by 27,673 m^(2) during 2000-2020,but it is projected to increase by 13,273,438,and 68 m^(2)under the SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios,respectively.We also observed remarkable spatial differences in ESs and ERs between past and future scenarios.For instance,the source area of the URYR exhibited high ESs and low ERs(P<0.001),while the ESs and ERs are declining and increasing,respectively,in the northeastern URYR(P<0.05).Finally,we proposed a spatial optimization framework to improve ESs and reduce ERs,which will support regional sustainable development.展开更多
Grassland degradation presents overwhelming challenges to biodiversity,ecosystem services,and the socioeconomic sustainability of dependent communities.However,a comprehensive synthesis of global knowledge on the fron...Grassland degradation presents overwhelming challenges to biodiversity,ecosystem services,and the socioeconomic sustainability of dependent communities.However,a comprehensive synthesis of global knowledge on the frontiers and key areas of grassland degradation research has not been achieved due to the limitations of traditional scientometrics methods.The present synthesis of information employed BERTopic,an advanced natural language processing tool,to analyze the extensive ecological literature on grassland degradation.We compiled a dataset of 4,504 publications from the Web of Science core collection database and used it to evaluate the geographic distribution and temporal evolution of different grassland types and available knowledge on the subject.Our analysis identified key topics in the global grassland degradation research domain,including the effects of grassland degradation on ecosystem functions,grassland ecological restoration and biodiversity conservation,erosion processes and hydrological models in grasslands,and others.The BERTopic analysis significantly outperforms traditional methods in identifying complex and evolving topics in large datasets of literature.Compared to traditional scientometrics analysis,BERTopic provides a more comprehensive perspective on the research areas,revealing not only popular topics but also emerging research areas that traditional methods may overlook,although scientometrics offers more specificity and detail.Therefore,we argue for the simultaneous use of both approaches to achieve more systematic and comprehensive assessments of specific research areas.This study represents an emerging application of BERTopic algorithms in ecological research,particularly in the critical research focused on global grassland degradation.It also highlights the need for integrating advanced computational methods in ecological research in this era of data explosion.Tools like the BERTopic algorithm are essential for enhancing our understanding of complex environmental problems,and it marks an important stride towards more sophisticated,data-driven analysis in ecology.展开更多
Tethyan Ocean was initially proposed by Austrian geologist Eduard Suess in 1893. The study of the Tethyan evolution by European geologists has led to the development of modern geology, but not to the establishment of ...Tethyan Ocean was initially proposed by Austrian geologist Eduard Suess in 1893. The study of the Tethyan evolution by European geologists has led to the development of modern geology, but not to the establishment of plate tectonics theory(Trümpy, 2001). With the progress in various studies, the concept of Tethys has evolved from a Mesozoic ocean into three long-term evolving oceans:Proto-Tethys, Paleo-Tethys, and Neo-Tethys (Figure 1), and their life cycles cover the entire Phanerozoic era (Wu et al., 2020).展开更多
Historical biome changes on the Tibetan Plateau provide important information that improves our understanding of the alpine vegetation responses to climate changes.However,a comprehensively quantitative reconstruction...Historical biome changes on the Tibetan Plateau provide important information that improves our understanding of the alpine vegetation responses to climate changes.However,a comprehensively quantitative reconstruction of the historical Tibetan Plateau biomes is not possible due to the lack of quantitative methods that enable appropriate classification of alpine biomes based on proxy data such as fossil pollen records.In this study,a pollen-based biome classification model was developed by applying a random forest algorithm(a supervised machine learning method)based on modern pollen assemblages on and around the Tibetan Plateau,and its robustness was assessed by comparing its results with the predictions of the biomisation method.The results indicated that modern biome distributions reconstructed using the random forest model based on modern pollen data generally concurred with the observed zonal vegetation.The random forest model had a significantly higher accuracy than the biomisation method,indicating the former is a more suitable tool for reconstructing alpine biome changes on the Tibetan Plateau.The random forest model was then applied to reconstruct the Tibetan Plateau biome changes from 22 ka BP to the present based on 51 fossil pollen records.The reconstructed biome distribution changes on the Tibetan Plateau generally corresponded to global climate changes and Asian monsoon variations.In the Last Glacial Maximum,the Tibetan Plateau was mainly desert with subtropical forests distributed in the southeast.During the last deglaciation,the alpine steppe began expanding and gradually became zonal vegetation in the central and eastern regions.Alpine meadow occupied the eastern and southeastern areas of the Tibetan Plateau since the early Holocene,and the forest-meadow-steppe-desert pattern running southeast to northwest on the Tibetan Plateau was established afterwards.In the mid-Holocene,subtropical forests extended north,which reflected the“optimum”condition.During the late Holocene,alpine meadows and alpine steppes expanded south.展开更多
Surface nanostructures(surface ion track)such as multiple nanodots or/and groove could be produced by single heavy ions(SHIs),when some materials are irradiated with SHIs under grazing incidence.The creation of equall...Surface nanostructures(surface ion track)such as multiple nanodots or/and groove could be produced by single heavy ions(SHIs),when some materials are irradiated with SHIs under grazing incidence.The creation of equally spaced nanodots on the surface of the irradiated SrTiO_(3)single crystal with grazing SHIs was previously explained as the periodic oscillation of electronic energy loss^([1]).展开更多
Peatlands, though covering only 3% of the earth surface, contain 300–400 pg carbon (C) and account for ∼30% of the global soil C pool [1], [2]. Global warming would influence the CH4 release from peatlands through a...Peatlands, though covering only 3% of the earth surface, contain 300–400 pg carbon (C) and account for ∼30% of the global soil C pool [1], [2]. Global warming would influence the CH4 release from peatlands through accelerating the fermentation of large quantities of long-accumulated soil organic carbon to CH4 by microorganisms particularly methanogens [3]. However, the ultimate CH4 budget in peatlands under the global warming scenario is also determined by changes in the CH4 oxidation activity of the methanotrophs [4]. Thus, identifications of active methanogens and methanotrophs, as well as their metabolic potentials in peatlands, are essential for understanding the overall peatland feedback to global warming.展开更多
基金supported by the Ecological Conservation and High-Quality Development of the Yellow River Basin Program,China(2022-YRUC-010102)the Second Tibetan Plateau Scientific Expedition and Research Program,China(20190ZKK0405)the Basic Research Fund Project of Innovation Team of Novel Forage Germplasm and Sustainable Utilization of Grassland Resources,China(BR22-12-07)。
文摘There is growing interest in introducing ecological risks(ERs)and ecosystem services(ESs)into environmental policies and practices.However,the integration of ESs and ERs into actual decision-making remains insufficient.We simulated the spatiotemporal dynamics of ESs(e.g.,carbon storage,water yield,habitat quality,and soil conservation)and ERs in the upper reach of the Yellow River(URYR)from 2000 to 2100.Additionally,we explored their relationships by combining the InVEST model and a landscape ecological risk model with CMIP6 data.Our main findings showed that regional ERs change in response to land use and environmental dynamics.Specifically,the ER area decreased by 27,673 m^(2) during 2000-2020,but it is projected to increase by 13,273,438,and 68 m^(2)under the SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios,respectively.We also observed remarkable spatial differences in ESs and ERs between past and future scenarios.For instance,the source area of the URYR exhibited high ESs and low ERs(P<0.001),while the ESs and ERs are declining and increasing,respectively,in the northeastern URYR(P<0.05).Finally,we proposed a spatial optimization framework to improve ESs and reduce ERs,which will support regional sustainable development.
基金financially supported by the First-Class Curriculum Program at the School of Economics and Management,University of the Chinese Academy of Sciencesthe National Natural Science Foundation of China(42041005)the National Social Science Foundation of China(23BTQ054)。
文摘Grassland degradation presents overwhelming challenges to biodiversity,ecosystem services,and the socioeconomic sustainability of dependent communities.However,a comprehensive synthesis of global knowledge on the frontiers and key areas of grassland degradation research has not been achieved due to the limitations of traditional scientometrics methods.The present synthesis of information employed BERTopic,an advanced natural language processing tool,to analyze the extensive ecological literature on grassland degradation.We compiled a dataset of 4,504 publications from the Web of Science core collection database and used it to evaluate the geographic distribution and temporal evolution of different grassland types and available knowledge on the subject.Our analysis identified key topics in the global grassland degradation research domain,including the effects of grassland degradation on ecosystem functions,grassland ecological restoration and biodiversity conservation,erosion processes and hydrological models in grasslands,and others.The BERTopic analysis significantly outperforms traditional methods in identifying complex and evolving topics in large datasets of literature.Compared to traditional scientometrics analysis,BERTopic provides a more comprehensive perspective on the research areas,revealing not only popular topics but also emerging research areas that traditional methods may overlook,although scientometrics offers more specificity and detail.Therefore,we argue for the simultaneous use of both approaches to achieve more systematic and comprehensive assessments of specific research areas.This study represents an emerging application of BERTopic algorithms in ecological research,particularly in the critical research focused on global grassland degradation.It also highlights the need for integrating advanced computational methods in ecological research in this era of data explosion.Tools like the BERTopic algorithm are essential for enhancing our understanding of complex environmental problems,and it marks an important stride towards more sophisticated,data-driven analysis in ecology.
文摘Tethyan Ocean was initially proposed by Austrian geologist Eduard Suess in 1893. The study of the Tethyan evolution by European geologists has led to the development of modern geology, but not to the establishment of plate tectonics theory(Trümpy, 2001). With the progress in various studies, the concept of Tethys has evolved from a Mesozoic ocean into three long-term evolving oceans:Proto-Tethys, Paleo-Tethys, and Neo-Tethys (Figure 1), and their life cycles cover the entire Phanerozoic era (Wu et al., 2020).
基金supported by the National Natural Science Foundation of China(Grant No.41690113)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA20070101)the National Natural Science Foundation of China(Grant Nos.42071114,41977395,and 41671202)。
文摘Historical biome changes on the Tibetan Plateau provide important information that improves our understanding of the alpine vegetation responses to climate changes.However,a comprehensively quantitative reconstruction of the historical Tibetan Plateau biomes is not possible due to the lack of quantitative methods that enable appropriate classification of alpine biomes based on proxy data such as fossil pollen records.In this study,a pollen-based biome classification model was developed by applying a random forest algorithm(a supervised machine learning method)based on modern pollen assemblages on and around the Tibetan Plateau,and its robustness was assessed by comparing its results with the predictions of the biomisation method.The results indicated that modern biome distributions reconstructed using the random forest model based on modern pollen data generally concurred with the observed zonal vegetation.The random forest model had a significantly higher accuracy than the biomisation method,indicating the former is a more suitable tool for reconstructing alpine biome changes on the Tibetan Plateau.The random forest model was then applied to reconstruct the Tibetan Plateau biome changes from 22 ka BP to the present based on 51 fossil pollen records.The reconstructed biome distribution changes on the Tibetan Plateau generally corresponded to global climate changes and Asian monsoon variations.In the Last Glacial Maximum,the Tibetan Plateau was mainly desert with subtropical forests distributed in the southeast.During the last deglaciation,the alpine steppe began expanding and gradually became zonal vegetation in the central and eastern regions.Alpine meadow occupied the eastern and southeastern areas of the Tibetan Plateau since the early Holocene,and the forest-meadow-steppe-desert pattern running southeast to northwest on the Tibetan Plateau was established afterwards.In the mid-Holocene,subtropical forests extended north,which reflected the“optimum”condition.During the late Holocene,alpine meadows and alpine steppes expanded south.
基金National Key research and Development Program of China(2022YFB3604001)National Natural Science Foundation of China(12075290,12035019)Youth Innovation Promotion Association of CAS(2020412)。
文摘Surface nanostructures(surface ion track)such as multiple nanodots or/and groove could be produced by single heavy ions(SHIs),when some materials are irradiated with SHIs under grazing incidence.The creation of equally spaced nanodots on the surface of the irradiated SrTiO_(3)single crystal with grazing SHIs was previously explained as the periodic oscillation of electronic energy loss^([1]).
基金supported by the Strategic Priority Research Program A of the Chinese Academy of Sciences (CAS) (XDA20050104)the Joint CAS-MPG Research Project (HZXM20225001MI)+2 种基金the National Natural Science Foundation of China (42041005)the Second Tibetan Plateau Scientific Expedition and Research (STEP) Program (2019QZKK0304)the Fundamental Research Funds for the Central Universities。
文摘Peatlands, though covering only 3% of the earth surface, contain 300–400 pg carbon (C) and account for ∼30% of the global soil C pool [1], [2]. Global warming would influence the CH4 release from peatlands through accelerating the fermentation of large quantities of long-accumulated soil organic carbon to CH4 by microorganisms particularly methanogens [3]. However, the ultimate CH4 budget in peatlands under the global warming scenario is also determined by changes in the CH4 oxidation activity of the methanotrophs [4]. Thus, identifications of active methanogens and methanotrophs, as well as their metabolic potentials in peatlands, are essential for understanding the overall peatland feedback to global warming.
